cs.AI - 人工智能
    cs.CL - 计算与语言
    cs.CR - 加密与安全
    cs.CV - 机器视觉与模式识别
    cs.CY - 计算与社会
    cs.DC - 分布式、并行与集群计算
    cs.GT - 计算机科学与博弈论
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.LO - 计算逻辑
    cs.MA - 多代理系统
    cs.MM - 多媒体
    cs.NE - 神经与进化计算
    cs.RO - 机器人学
    cs.SE - 软件工程
    cs.SI - 社交网络与信息网络
    econ.EM - 计量经济学
    eess.AS - 语音处理
    eess.IV - 图像与视频处理
    eess.SP - 信号处理
    math.OC - 优化与控制
    math.PR - 概率
    math.ST - 统计理论
    physics.flu-dyn - 流体动力学
    physics.soc-ph - 物理学与社会
    q-fin.ST - 统计金融学
    quant-ph - 量子物理
    stat.AP - 应用统计
    stat.CO - 统计计算
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cs.AI]An Educational System for Personalized Teacher Recommendation in K-12 Online Classrooms
    • [cs.AI]Applying the Case Difference Heuristic to Learn Adaptations from Deep Network Features
    • [cs.AI]Deep Reinforcement Learning based Dynamic Optimization of Bus Timetable
    • [cs.AI]Do Humans Trust Advice More if it Comes from AI? An Analysis of Human-AI Interactions
    • [cs.AI]Experimental Evidence that Empowerment May Drive Exploration in Sparse-Reward Environments
    • [cs.AI]Forgetting in Answer Set Programming — A Survey
    • [cs.AI]Genetic CFL: Optimization of Hyper-Parameters in Clustered Federated Learning
    • [cs.AI]Learning Mixed-Integer Linear Programs from Contextual Examples
    • [cs.AI]Trusting RoBERTa over BERT: Insights from CheckListing the Natural Language Inference Task
    • [cs.AI]Uncertainty-Aware Reliable Text Classification
    • [cs.AI]Understanding Factors Affecting Fuel Consumption of Vehicles Through Explainable Boosting Machines
    • [cs.CL]Annotation and Classification of Evidence and Reasoning Revisions in Argumentative Writing
    • [cs.CL]AutoBERT-Zero: Evolving BERT Backbone from Scratch
    • [cs.CL]CLSRIL-23: Cross Lingual Speech Representations for Indic Languages
    • [cs.CL]FLEX: Unifying Evaluation for Few-Shot NLP
    • [cs.CL]FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task
    • [cs.CL]FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark
    • [cs.CL]HTLM: Hyper-Text Pre-Training and Prompting of Language Models
    • [cs.CL]Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features
    • [cs.CL]Large-Scale News Classification using BERT Language Model: Spark NLP Approach
    • [cs.CL]Multi-Task Learning based Online Dialogic Instruction Detection with Pre-trained Language Models
    • [cs.CL]ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus
    • [cs.CL]Robust Learning for Text Classification with Multi-source Noise Simulation and Hard Example Mining
    • [cs.CL]Solving ESL Sentence Completion Questions via Pre-trained Neural Language Models
    • [cs.CL]Spanish Language Models
    • [cs.CL]TGIF: Tree-Graph Integrated-Format Parser for Enhanced UD with Two-Stage Generic- to Individual-Language Finetuning
    • [cs.CL]Tailor: Generating and Perturbing Text with Semantic Controls
    • [cs.CL]Transition-based Bubble Parsing: Improvements on Coordination Structure Prediction
    • [cs.CL]Turning Tables: Generating Examples from Semi-structured Tables for Endowing Language Models with Reasoning Skills
    • [cs.CL]Wordcraft: a Human-AI Collaborative Editor for Story Writing
    • [cs.CR]BlockJack: Towards Improved Prevention of IP Prefix Hijacking Attacks in Inter-Domain Routing Via Blockchain
    • [cs.CR]Improving Security in McAdams Coefficient-Based Speaker Anonymization by Watermarking Method
    • [cs.CV]A Generalized Framework for Edge-preserving and Structure-preserving Image Smoothing
    • [cs.CV]Adversarial Attacks on Multi-task Visual Perception for Autonomous Driving
    • [cs.CV]Amodal segmentation just like doing a jigsaw
    • [cs.CV]An Efficient and Small Convolutional Neural Network for Pest Recognition — ExquisiteNet
    • [cs.CV]CMT: Convolutional Neural Networks Meet Vision Transformers
    • [cs.CV]COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing
    • [cs.CV]Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains
    • [cs.CV]Deep Automatic Natural Image Matting
    • [cs.CV]Deep Learning based Food Instance Segmentation using Synthetic Data
    • [cs.CV]Diff-Net: Image Feature Difference based High-Definition Map Change Detection
    • [cs.CV]DynaDog+T: A Parametric Animal Model for Synthetic Canine Image Generation
    • [cs.CV]FetalNet: Multi-task deep learning framework for fetal ultrasound biometric measurements
    • [cs.CV]From Show to Tell: A Survey on Image Captioning
    • [cs.CV]HDMapNet: An Online HD Map Construction and Evaluation Framework
    • [cs.CV]High carbon stock mapping at large scale with optical satellite imagery and spaceborne LIDAR
    • [cs.CV]Incorporating Lambertian Priors into Surface Normals Measurement
    • [cs.CV]Level generation and style enhancement — deep learning for game development overview
    • [cs.CV]Lidar Light Scattering Augmentation (LISA): Physics-based Simulation of Adverse Weather Conditions for 3D Object Detection
    • [cs.CV]MeNToS: Tracklets Association with a Space-Time Memory Network
    • [cs.CV]Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translation
    • [cs.CV]Neighbor-view Enhanced Model for Vision and Language Navigation
    • [cs.CV]Object Retrieval and Localization in Large Art Collections using Deep Multi-Style Feature Fusion and Iterative Voting
    • [cs.CV]Passive attention in artificial neural networks predicts human visual selectivity
    • [cs.CV]Potential UAV Landing Sites Detection through Digital Elevation Models Analysis
    • [cs.CV]Recurrent Parameter Generators
    • [cs.CV]STAR: Sparse Transformer-based Action Recognition
    • [cs.CV]Scalable Surface Reconstruction with Delaunay-Graph Neural Networks
    • [cs.CV]Semantic Image Cropping
    • [cs.CV]Single-image Full-body Human Relighting
    • [cs.CV]StyleFusion: A Generative Model for Disentangling Spatial Segments
    • [cs.CV]StyleVideoGAN: A Temporal Generative Model using a Pretrained StyleGAN
    • [cs.CV]Surgical Instruction Generation with Transformers
    • [cs.CV]Training Compact CNNs for Image Classification using Dynamic-coded Filter Fusion
    • [cs.CV]Training for temporal sparsity in deep neural networks, application in video processing
    • [cs.CV]Unsupervised Anomaly Instance Segmentation for Baggage Threat Recognition
    • [cs.CV]Variational Topic Inference for Chest X-Ray Report Generation
    • [cs.CV]What Image Features Boost Housing Market Predictions?
    • [cs.CV]What and When to Look?: Temporal Span Proposal Network for Video Visual Relation Detection
    • [cs.CY]Auditing for Diversity using Representative Examples
    • [cs.CY]Predicting market inflation expectations with news topics and sentiment
    • [cs.DC]A Byzantine Fault-Tolerant Consensus Library for Hyperledger Fabric
    • [cs.DC]A64FX — Your Compiler You Must Decide!
    • [cs.DC]Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines
    • [cs.DC]Efficient Resources Distribution for an Ephemeral Cloud/Edge continuum
    • [cs.DC]Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization
    • [cs.DC]MXDAG: A Hybrid Abstraction for Cluster Applications
    • [cs.DC]Scalable Biophysical Simulations of the Neuromuscular System
    • [cs.GT]DiRe Committee : Diversity and Representation Constraints in Multiwinner Elections
    • [cs.GT]Optimal Scoring Rule Design
    • [cs.GT]Two-Sided Matching Meets Fair Division
    • [cs.HC]Identifying Competition and Mutualism Between Online Groups
    • [cs.IR]Auto-detecting groups based on textual similarity for group recommendations
    • [cs.IR]Next-item Recommendations in Short Sessions
    • [cs.IR]Online Learning for Recommendations at Grubhub
    • [cs.IR]Recommending best course of treatment based on similarities of prognostic markers\thanks{All authors contributed equally
    • [cs.IR]Scene-adaptive Knowledge Distillation for Sequential Recommendation via Differentiable Architecture Search
    • [cs.IT]今日学术视野(2021.7.17) - 图1-Norm Minimization for Joint Precoding and Peak-to-Average-Power Ratio Reduction
    • [cs.IT]A Bayesian Compressive Sensing Approach to Robust Near-Field Antenna Characterization
    • [cs.IT]Computing Permanents on a Trellis
    • [cs.IT]Data Disclosure with Non-zero Leakage and Non-invertible Leakage Matrix
    • [cs.IT]Frequency-Time Division based Deep Learning for OFDM Channel Estimation
    • [cs.IT]Joint CFO, Gridless Channel Estimation and Data Detection for Underwater Acoustic OFDM Systems
    • [cs.IT]Moufang Patterns and Geometry of Information
    • [cs.IT]On Hard and Soft Decision Decoding of BCH Codes
    • [cs.IT]Support Constrained Generator Matrices and the Generalized Hamming Weights
    • [cs.IT]The Feedback Capacity of Noisy Output is the STate (NOST) Channels
    • [cs.IT]Trade-Based LDPC Codes
    • [cs.IT]Twisted Reed-Solomon Codes
    • [cs.LG]A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
    • [cs.LG]A Reinforcement Learning Environment for Mathematical Reasoning via Program Synthesis
    • [cs.LG]A Robust Deep Learning Workflow to Predict Multiphase Flow Behavior during Geological CO2 Sequestration Injection and Post-Injection Periods
    • [cs.LG]A multi-schematic classifier-independent oversampling approach for imbalanced datasets
    • [cs.LG]Adaptable Agent Populations via a Generative Model of Policies
    • [cs.LG]Algorithmic Concept-based Explainable Reasoning
    • [cs.LG]Copula-Based Normalizing Flows
    • [cs.LG]Data vs classifiers, who wins?
    • [cs.LG]DeFed: A Principled Decentralized and Privacy-Preserving Federated Learning Algorithm
    • [cs.LG]Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo
    • [cs.LG]Expert Graphs: Synthesizing New Expertise via Collaboration
    • [cs.LG]Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests
    • [cs.LG]Hierarchical graph neural nets can capture long-range interactions
    • [cs.LG]Hybrid Bayesian Neural Networks with Functional Probabilistic Layers
    • [cs.LG]Input Dependent Sparse Gaussian Processes
    • [cs.LG]Kernel Continual Learning
    • [cs.LG]Lockout: Sparse Regularization of Neural Networks
    • [cs.LG]MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators
    • [cs.LG]MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning
    • [cs.LG]MultiBench: Multiscale Benchmarks for Multimodal Representation Learning
    • [cs.LG]NeuSaver: Neural Adaptive Power Consumption Optimization for Mobile Video Streaming
    • [cs.LG]On the expressivity of bi-Lipschitz normalizing flows
    • [cs.LG]Only Train Once: A One-Shot Neural Network Training And Pruning Framework
    • [cs.LG]PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration
    • [cs.LG]Randomized ReLU Activation for Uncertainty Estimation of Deep Neural Networks
    • [cs.LG]Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks
    • [cs.LG]Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box setting
    • [cs.LG]USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems
    • [cs.LG]You Do Not Need a Bigger Boat: Recommendations at Reasonable Scale in a (Mostly) Serverless and Open Stack
    • [cs.LO]Proceedings of the Sixteenth Workshop on Logical Frameworks and Meta-Languages: Theory and Practice
    • [cs.MA]Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
    • [cs.MM]Cross-modal Variational Auto-encoder for Content-based Micro-video Background Music Recommendation
    • [cs.NE]Motor Imagery Classification based on CNN-GRU Network with Spatio-Temporal Feature Representation
    • [cs.NE]Neural Architecture Search using Covariance Matrix Adaptation Evolution Strategy
    • [cs.NE]Preference Incorporation into Many-Objective Optimization: An Outranking-based Ant Colony Algorithm
    • [cs.NE]Transformer-based Machine Learning for Fast SAT Solvers and Logic Synthesis
    • [cs.RO]A Low-Complexity Radar Detector Outperforming OS-CFAR for Indoor Drone Obstacle Avoidance
    • [cs.RO]A life-long SLAM approach using adaptable local maps based on rasterized LIDAR images
    • [cs.RO]An End-to-End Differentiable Framework for Contact-Aware Robot Design
    • [cs.RO]Collision Avoidance Using Spherical Harmonics
    • [cs.RO]Conflict-free Cooperation Method for Connected and Automated Vehicles at Unsignalized Intersections: Graph-based Modeling and Optimality Analysis
    • [cs.RO]Deformable Ela
    5892
    sto-Plastic Object Shaping using an Elastic Hand and Model-Based Reinforcement Learning
    • [cs.RO]Design of Distributed Reconfigurable Robotics Systems with ReconROS
    • [cs.RO]GI-NNet & RGI-NNet: Development of Robotic Grasp Pose Models, Trainable with Large as well as Limited Labelled Training Datasets, under supervised and semi supervised paradigms
    • [cs.RO]High-level Decisions from a Safe Maneuver Catalog with Reinforcement Learning for Safe and Cooperative Automated Merging
    • [cs.RO]Learning Sparse Interaction Graphs of Partially Observed Pedestrians for Trajectory Prediction
    • [cs.RO]Minimizing Safety Interference for Safe an
    a07
    d Comfortable Automated Driving with Distributional Reinforcement Learning
    • [cs.RO]On nondeterminism in combinatorial filters
    • [cs.RO]OpenCDA:An Open Cooperative Driving Automation Framework Integrated with Co-Simulation
    • [cs.RO]Optimization-Based Quadrupedal Hybrid Wheeled-Legged Locomotion
    • [cs.RO]Personalizing User Engagement Dynamics in a Non-Verbal Communication Game for Cerebral Palsy
    • [cs.RO]Real-Time Grasping Strategies Using Event Camera
    • [cs.RO]Rule-based Evaluation and Optimal Control for Autonomous Driving
    • [cs.RO]Sensorimotor-inspired Tactile Feedback and Control Improve Consistency of Prosthesis Manipulation in the Absence of Direct Vision
    • [cs.RO]VILENS: Visual, Inertial, Lidar, and Leg Odometry for All-Terrain Legged Robots
    • [cs.RO]Vision-Based Target Localization for a Flapping-Wing Aerial Vehicle
    • [cs.SE]Empowered and Embedded: Ethics and Agile Processes
    • [cs.SE]Neural Code Summarization: How Far Are We?
    • [cs.SE]Reel Life vs. Real Life: How Software Developers Share Their Daily Life through Vlogs
    • [cs.SI]Clustering of heterogeneous populations of networks
    • [cs.SI]Look who’s watching: platform labels and user engagement on state-backed media outlets
    • [cs.SI]Should I Stay or Should I Go: Predicting Changes in Cluster Membership
    • [econ.EM]Generalized Covariance Estimator
    • [eess.AS]VAD-free Streaming Hybrid CTC/Attention ASR for Unsegmented Recording
    • [eess.IV]A modular U-Net for automated segmentation of X-ray tomography images in composite materials
    • [eess.IV]End-to-end Ultrasound Frame to Volume Registration
    • [eess.IV]Multi-Channel Auto-Encoders and a Novel Dataset for Learning Domain Invariant Representations of Histopathology Images
    • [eess.IV]RCDNet: An Interpretable Rain Convolutional Dictionary Network for Single Image Deraining
    • [eess.SP]Frequency-packed Faster-than-Nyquist Signaling via Symbol-level Precoding for Multi-user MISO Redundant Transmissions
    • [eess.SP]Multiclass Permanent Magnets Superstructure for Indoor Localization using Artificial Intelligence
    • [eess.SP]Optimality of the Discrete Fourier Transform for Beamspace Massive MU-MIMO Communication
    • [math.OC]Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update
    • [math.PR]Determinantal Point Processes in the Flat Limit
    • [math.PR]Performance of Bayesian linear regression in a model with mismatch
    • [math.ST]On the early solution path of best subset selection
    • [math.ST]The Completion of Covariance Kernels
    • [math.ST]The Information Projection in Moment Inequality Models: Existence, Dual Representation, and Approximation
    • [physics.flu-dyn]Predicting the near-wall region of turbulence through convolutional neural networks
    • [physics.soc-ph]Deep learning based parameter search for an agent based social network model
    • [physics.soc-ph]From Reddit to Wall Street: The role of committed minorities in financial collective action
    • [q-fin.ST]Credit scoring using neural networks and SURE posterior probability calibration
    • [quant-ph]A Combinatorial Interpretation for the Shor-Laflamme Weight Enumerators of CWS Codes
    • [quant-ph]Szegedy Walk Unitaries for Quantum Maps
    • [stat.AP]Statistical modeling of corneal OCT speckle. A distributional model-free approach
    • [stat.CO]A comparison of nonlinear extensions to the ensemble Kalman filter: Gaussian Anamorphosis and Two-Step Ensemble Filters
    • [stat.ME]A new class of conditional Markov jump processes with regime switching and path dependence: properties and maximum likelihood estimation
    • [stat.ME]Covariate adjustment in randomised trials: canonical link functions protect against model mis-specification
    • [stat.ME]Estimation of spatially varying parameters with application to hyperbolic SPDEs
    • [stat.ME]Independence weights for causal inference with continuous exposures
    • [stat.ME]Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces
    • [stat.ME]Nonparametric, tuning-free estimation of S-shaped functions
    • [stat.ME]Personalized and Reliable Decision Sets: Enhancing Interpretability in Clinical Decision Support Systems
    • [stat.ME]Statistical inference using Regularized M-estimation in the reproducing kernel Hilbert space for handling missing data
    • [stat.ME]Temporally Local Maximum Likelihood with Application to SIS Model
    • [stat.ME]The Taxicab Sampler: MCMC for Discrete Spaces with Application to Tree Models
    • [stat.ML]A unified framework for bandit multiple testing
    • [stat.ML]Entropic Inequality Constraints from 今日学术视野(2021.7.17) - 图2-separation Relations in Directed Acyclic Graphs with Hidden Variables
    • [stat.ML]FastSHAP: Real-Time Shapley Value Estimation
    • [stat.ML]Hida-Matérn Kernel
    • [stat.ML]Mid-flight Forecasting for CPA Lines in Online Advertising
    • [stat.ML]Multi-label Chaining with Imprecise Probabilities
    • [stat.ML]Principal component analysis for Gaussian process posteriors

    ·····································

    • [cs.AI]An Educational System for Personalized Teacher Recommendation in K-12 Online Classrooms
    Jiahao Chen, Hang Li, Wenbiao Ding, Zitao Liu
    http://arxiv.org/abs/2107.07124v1

    • [cs.AI]Applying the Case Difference Heuristic to Learn Adaptations from Deep Network Features
    Xiaomeng Ye, Ziwei Zhao, David Leake, Xizi Wang, David Crandall
    http://arxiv.org/abs/2107.07095v1

    • [cs.AI]Deep Reinforcement Learning based Dynamic Optimization of Bus Timetable
    Guanqun Ai, Xingquan Zuo, Gang chen, Binglin Wu
    http://arxiv.org/abs/2107.07066v1

    • [cs.AI]Do Humans Trust Advice More if it Comes from AI? An Analysis of Human-AI Interactions
    Kailas Vodrahalli, Tobias Gerstenberg, James Zou
    http://arxiv.org/abs/2107.07015v1

    • [cs.AI]Experimental Evidence that Empowerment May Drive Exploration in Sparse-Reward Environments
    Francesco Massari, Martin Biehl, Lisa Meeden, Ryota Kanai
    http://arxiv.org/abs/2107.07031v1

    • [cs.AI]Forgetting in Answer Set Programming — A Survey
    Ricardo Gonçalves, Matthias Knorr, João Leite
    http://arxiv.org/abs/2107.07016v1

    • [cs.AI]Genetic CFL: Optimization of Hyper-Parameters in Clustered Federated Learning
    Shaashwat Agrawal, Sagnik Sarkar, Mamoun Alazab, Praveen Kumar Reddy Maddikunta, Thippa Reddy Gadekallu, Quoc-Viet Pham
    http://arxiv.org/abs/2107.07233v1

    • [cs.AI]Learning Mixed-Integer Linear Programs from Contextual Examples
    Mohit Kumar, Samuel Kolb, Luc De Raedt, Stefano Teso
    http://arxiv.org/abs/2107.07136v1

    • [cs.AI]Trusting RoBERTa over BERT: Insights from CheckListing the Natural Language Inference Task
    Ishan Tarunesh, Somak Aditya, Monojit Choudhury
    http://arxiv.org/abs/2107.07229v1

    • [cs.AI]Uncertainty-Aware Reliable Text Classification
    Yibo Hu, Latifur Khan
    http://arxiv.org/abs/2107.07114v1

    • [cs.AI]Understanding Factors Affecting Fuel Consumption of Vehicles Through Explainable Boosting Machines
    Alberto Barbado, Óscar Corcho
    http://arxiv.org/abs/2107.06031v2

    • [cs.CL]Annotation and Classification of Evidence and Reasoning Revisions in Argumentative Writing
    Tazin Afrin, Elaine Wang, Diane Litman, Lindsay C. Matsumura, Richard Correnti
    http://arxiv.org/abs/2107.06990v1

    • [cs.CL]AutoBERT-Zero: Evolving BERT Backbone from Scratch
    Jiahui Gao, Hang Xu, Han shi, Xiaozhe Ren, Philip L. H. Yu, Xiaodan Liang, Xin Jiang, Zhenguo Li
    http://arxiv.org/abs/2107.07445v1

    • [cs.CL]CLSRIL-23: Cross Lingual Speech Representations for Indic Languages
    Anirudh Gupta, Harveen Singh Chadha, Priyanshi Shah, Neeraj Chimmwal, Ankur Dhuriya, Rishabh Gaur, Vivek Raghavan
    http://arxiv.org/abs/2107.07402v1

    • [cs.CL]FLEX: Unifying Evaluation for Few-Shot NLP
    Jonathan Bragg, Arman Cohan, Kyle Lo, Iz Beltagy
    http://arxiv.org/abs/2107.07170v1

    • [cs.CL]FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task
    Yun Tang, Hongyu Gong, Xian Li, Changhan Wang, Juan Pino, Holger Schwenk, Naman Goyal
    http://arxiv.org/abs/2107.06959v1

    • [cs.CL]FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark
    Liang Xu, Xiaojing Lu, Chenyang Yuan, Xuanwei Zhang, Hu Yuan, Huilin Xu, Guoao Wei, Xiang Pan, Hai Hu
    http://arxiv.org/abs/2107.07498v1

    • [cs.CL]HTLM: Hyper-Text Pre-Training and Prompting of Language Models
    Armen Aghajanyan, Dmytro Okhonko, Mike Lewis, Mandar Joshi, Hu Xu, Gargi Ghosh, Luke Zettlemoyer
    http://arxiv.org/abs/2107.06955v1

    • [cs.CL]Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features
    Hannah Rashkin, David Reitter, Gaurav Singh Tomar, Dipanjan Das
    http://arxiv.org/abs/2107.06963v1

    • [cs.CL]Large-Scale News Classification using BERT Language Model: Spark NLP Approach
    Kuncahyo Setyo Nugroho, Anantha Yullian Sukmadewa, Novanto Yudistira
    http://arxiv.org/abs/2107.06785v2

    • [cs.CL]Multi-Task Learning based Online Dialogic Instruction Detection with Pre-trained Language Models
    Yang Hao, Hang Li, Wenbiao Ding, Zhongqin Wu, Jiliang Tang, Rose Luckin, Zitao Liu
    http://arxiv.org/abs/2107.07119v1

    • [cs.CL]ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus
    Ayyoob Imani, Masoud Jalili Sabet, Philipp Dufter, Michael Cysouw, Hinrich Schütze
    http://arxiv.org/abs/2107.06632v2

    • [cs.CL]Robust Learning for Text Classification with Multi-source Noise Simulation and Hard Example Mining
    Guowei Xu, Wenbiao Ding, Weiping Fu, Zhongqin Wu
    http://arxiv.org/abs/2107.07113v1

    • [cs.CL]Solving ESL Sentence Completion Questions via Pre-trained Neural Language Models
    Qiongqiong Liu, Tianqiao Liu, Jiafu Zhao, Qiang Fang, Wenbiao Ding, Zhongqin Wu, Feng Xia, Jiliang Tang, Zitao Liu
    http://arxiv.org/abs/2107.07122v1

    • [cs.CL]Spanish Language Models
    Asier Gutiérrez-Fandiño, Jordi Armengol-Estapé, Marc Pàmies, Joan Llop-Palao, Joaquín Silveira-Ocampo, Casimiro Pio Carrino, Aitor Gonzalez-Agirre, Carme Armentano-Oller, Carlos Rodriguez-Penagos, Marta Villegas
    http://arxiv.org/abs/2107.07253v1

    • [cs.CL]TGIF: Tree-Graph Integrated-Format Parser for Enhanced UD with Two-Stage Generic- to Individual-Language Finetuning
    Tianze Shi, Lillian Lee
    http://arxiv.org/abs/2107.06907v1

    • [cs.CL]Tailor: Generating and Perturbing Text with Semantic Controls
    Alexis Ross, Tongshuang Wu, Hao Peng, Matthew E. Peters, Matt Gardner
    http://arxiv.org/abs/2107.07150v1

    • [cs.CL]Transition-based Bubble Parsing: Improvements on Coordination Structure Prediction
    Tianze Shi, Lillian Lee
    http://arxiv.org/abs/2107.06905v1

    • [cs.CL]Turning Tables: Generating Examples from Semi-structured Tables for Endowing Language Models with Reasoning Skills
    Ori Yoran, Alon Talmor, Jonathan Berant
    http://arxiv.org/abs/2107.07261v1

    • [cs.CL]Wordcraft: a Human-AI Collaborative Editor for Story Writing
    Andy Coenen, Luke Davis, Daphne Ippolito, Emily Reif, Ann Yuan
    http://arxiv.org/abs/2107.07430v1

    • [cs.CR]BlockJack: Towards Improved Prevention of IP Prefix Hijacking Attacks in Inter-Domain Routing Via Blockchain
    I Wayan Budi Sentana, Muhammad Ikram, Mohamed Ali Kaafar
    http://arxiv.org/abs/2107.07063v1

    • [cs.CR]Improving Security in McAdams Coefficient-Based Speaker Anonymization by Watermarking Method
    Candy Olivia Mawalim, Masashi Unoki
    http://arxiv.org/abs/2107.07223v1

    • [cs.CV]A Generalized Framework for Edge-preserving and Structure-preserving Image Smoothing
    Wei Liu, Pingping Zhang, Yinjie Lei, Xiaolin Huang, Jie Yang, Michael Ng
    http://arxiv.org/abs/2107.07058v1

    • [cs.CV]Adversarial Attacks on Multi-task Visual Perception for Autonomous Driving
    Ibrahim Sobh, Ahmed Hamed, Varun Ravi Kumar, Senthil Yogamani
    http://arxiv.org/abs/2107.07449v1

    • [cs.CV]Amodal segmentation just like doing a jigsaw
    Xunli Zeng, Jianqin Yin
    http://arxiv.org/abs/2107.07464v1

    • [cs.CV]An Efficient and Small Convolutional Neural Network for Pest Recognition — ExquisiteNet
    Shi-Yao Zhou, Chung-Yen Su
    http://arxiv.org/abs/2107.07167v1

    • [cs.CV]CMT: Convolutional Neural Networks Meet Vision Transformers
    Jianyuan Guo, Kai Han, Han Wu, Chang Xu, Yehui Tang, Chunjing Xu, Yunhe Wang
    http://arxiv.org/abs/2107.06263v2

    • [cs.CV]COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing
    Di You, Jian Zhang, Jingfen Xie, Bin Chen, Siwei Ma
    http://arxiv.org/abs/2107.07225v1

    • [cs.CV]Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains
    Puneet Mangla, Shivam Chandhok, Vineeth N Balasubramanian, Fahad Shahbaz Khan
    http://arxiv.org/abs/2107.07497v1

    • [cs.CV]Deep Automatic Natural Image Matting
    Jizhizi Li, Jing Zhang, Dacheng Tao
    http://arxiv.org/abs/2107.07235v1

    • [cs.CV]Deep Learning based Food Instance Segmentation using Synthetic Data
    D. Park, J. Lee, J. Lee, K. Lee
    http://arxiv.org/abs/2107.07191v1

    • [cs.CV]Diff-Net: Image Feature Difference based High-Definition Map Change Detection
    Lei He, Shengjie Jiang, Xiaoqing Liang, Ning Wang, Shiyu Song
    http://arxiv.org/abs/2107.07030v1

    • [cs.CV]DynaDog+T: A Parametric Animal Model for Synthetic Canine Image Generation
    Jake Deane, Sinead Kearney, Kwang In Kim, Darren Cosker
    http://arxiv.org/abs/2107.07330v1

    • [cs.CV]FetalNet: Multi-task deep learning framework for fetal ultrasound biometric measurements
    Szymon Płotka, Tomasz Włodarczyk, Adam Klasa, Michał Lipa, Arkadiusz Sitek, Tomasz Trzciński
    http://arxiv.org/abs/2107.06943v1

    • [cs.CV]From Show to Tell: A Survey on Image Captioning
    Matteo Stefanini, Marcella Cornia, Lorenzo Baraldi, Silvia Cascianelli, Giuseppe Fiameni, Rita Cucchiara
    http://arxiv.org/abs/2107.06912v1

    • [cs.CV]HDMapNet: An Online HD Map Construction and Evaluation Framework
    Qi Li, Yue Wang, Yilun Wang, Hang Zhao
    http://arxiv.org/abs/2107.06307v2

    • [cs.CV]High carbon stock mapping at large scale with optical satellite imagery and spaceborne LIDAR
    Nico Lang, Konrad Schindler, Jan Dirk Wegner
    http://arxiv.org/abs/2107.07431v1

    • [cs.CV]Incorporating Lambertian Priors into Surface Normals Measurement
    Yakun Ju, Muwei Jian, Shaoxiang Guo, Yingyu Wang, Huiyu Zhou, Junyu Dong
    http://arxiv.org/abs/2107.07192v1

    • [cs.CV]Level generation and style enhancement — deep learning for game development overview
    Piotr Migdał, Bartłomiej Olechno, Błażej Podgórski
    http://arxiv.org/abs/2107.07397v1

    • [cs.CV]Lidar Light Scattering Augmentation (LISA): Physics-based Simulation of Adverse Weather Conditions for 3D Object Detection
    Velat Kilic, Deepti Hegde, Vishwanath Sindagi, A. Brinton Cooper, Mark A. Foster, Vishal M. Patel
    http://arxiv.org/abs/2107.07004v1

    • [cs.CV]MeNToS: Tracklets Association with a Space-Time Memory Network
    Mehdi Miah, Guillaume-Alexandre Bilodeau, Nicolas Saunier
    http://arxiv.org/abs/2107.07067v1

    • [cs.CV]Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translation
    Lalith Sharan, Gabriele Romano, Sven Koehler, Halvar Kelm, Matthias Karck, Raffaele De Simone, Sandy Engelhardt
    http://arxiv.org/abs/2107.06941v1

    • [cs.CV]Neighbor-view Enhanced Model for Vision and Language Navigation
    Dong An, Yuankai Qi, Yan Huang, Qi Wu, Liang Wang, Tieniu Tan
    http://arxiv.org/abs/2107.07201v1

    • [cs.CV]Object Retrieval and Localization in Large Art Collections using Deep Multi-Style Feature Fusion and Iterative Voting
    Nikolai Ufer, Sabine Lang, Björn Ommer
    http://arxiv.org/abs/2107.06935v1

    • [cs.CV]Passive attention in artificial neural networks predicts human visual selectivity
    Thomas A. Langlois, H. Charles Zhao, Erin Grant, Ishita Dasgupta, Thomas L. Griffiths, Nori Jacoby
    http://arxiv.org/abs/2107.07013v1

    • [cs.CV]Potential UAV Landing Sites Detection through Digital Elevation Models Analysis
    Efstratios Kakaletsis, Nikos Nikolaidis
    http://arxiv.org/abs/2107.06921v1

    • [cs.CV]Recurrent Parameter Generators
    Jiayun Wang, Yubei Chen, Stella X. Yu, Brian Cheung, Yann LeCun
    http://arxiv.org/abs/2107.07110v1

    • [cs.CV]STAR: Sparse Transformer-based Action Recognition
    Feng Shi, Chonghan Lee, Liang Qiu, Yizhou Zhao, Tianyi Shen, Shivran Muralidhar, Tian Han, Song-Chun Zhu, Vijaykrishnan Narayanan
    http://arxiv.org/abs/2107.07089v1

    • [cs.CV]Scalable Surface Reconstruction with Delaunay-Graph Neural Networks
    Raphael Sulzer, Loic Landrieu, Renaud Marlet, Bruno Vallet
    http://arxiv.org/abs/2107.06130v2

    • [cs.CV]Semantic Image Cropping
    Oriol Corcoll
    http://arxiv.org/abs/2107.07153v1

    • [cs.CV]Single-image Full-body Human Relighting
    Manuel Lagunas, Xin Sun, Jimei Yang, Ruben Villegas, Jianming Zhang, Zhixin Shu, Belen Masia, Diego Gutierrez
    http://arxiv.org/abs/2107.07259v1

    • [cs.CV]StyleFusion: A Generative Model for Disentangling Spatial Segments
    Omer Kafri, Or Patashnik, Yuval Alaluf, Daniel Cohen-Or
    http://arxiv.org/abs/2107.07437v1

    • [cs.CV]StyleVideoGAN: A Temporal Generative Model using a Pretrained StyleGAN
    Gereon Fox, Ayush Tewari, Mohamed Elgharib, Christian Theobalt
    http://arxiv.org/abs/2107.07224v1

    • [cs.CV]Surgical Instruction Generation with Transformers
    Jinglu Zhang, Yinyu Nie, Jian Chang, Jian Jun Zhang
    http://arxiv.org/abs/2107.06964v1

    • [cs.CV]Training Compact CNNs for Image Classification using Dynamic-coded Filter Fusion
    Mingbao Lin, Rongrong Ji, Bohong Chen, Fei Chao, Jianzhuang Liu, Wei Zeng, Yonghong Tian, Qi Tian
    http://arxiv.org/abs/2107.06916v1

    • [cs.CV]Training for temporal sparsity in deep neural networks, application in video processing
    Amirreza Yousefzadeh, Manolis Sifalakis
    http://arxiv.org/abs/2107.07305v1

    • [cs.CV]Unsupervised Anomaly Instance Segmentation for Baggage Threat Recognition
    Taimur Hassan, Samet Akcay, Mohammed Bennamoun, Salman Khan, Naoufel Werghi
    http://arxiv.org/abs/2107.07333v1

    • [cs.CV]Variational Topic Inference for Chest X-Ray Report Generation
    Ivona Najdenkoska, Xiantong Zhen, Marcel Worring, Ling Shao
    http://arxiv.org/abs/2107.07314v1

    • [cs.CV]What Image Features Boost Housing Market Predictions?
    Zona Kostic, Aleksandar Jevremovic
    http://arxiv.org/abs/2107.07148v1

    • [cs.CV]What and When to Look?: Temporal Span Proposal Network for Video Visual Relation Detection
    Sangmin Woo, Junhyug Noh, Kangil Kim
    http://arxiv.org/abs/2107.07154v1

    • [cs.CY]Auditing for Diversity using Representative Examples
    Vijay Keswani, L. Elisa Celis
    http://arxiv.org/abs/2107.07393v1

    • [cs.CY]Predicting market inflation expectations with news topics and sentiment
    Sonja Tilly, Giacomo Livan
    http://arxiv.org/abs/2107.07155v1

    • [cs.DC]A Byzantine Fault-Tolerant Consensus Library for Hyperledger Fabric
    Artem Barger, Yacov Manevich, Hagar Meir, Yoav Tock
    http://arxiv.org/abs/2107.06922v1

    • [cs.DC]A64FX — Your Compiler You Must Decide!
    Jens Domke
    http://arxiv.org/abs/2107.07157v1

    • [cs.DC]Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines
    Shigang Li, Torsten Hoefler
    http://arxiv.org/abs/2107.06925v1

    • [cs.DC]Efficient Resources Distribution for an Ephemeral Cloud/Edge continuum
    Emanuele Carlini, Patrizio Dazzi, Luca Ferrucci, Matteo Mordacchini
    http://arxiv.org/abs/2107.07195v1

    • [cs.DC]Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization
    Lipeng Wan, Axel Huebl, Junmin Gu, Franz Poeschel, Ana Gainaru, Ruonan Wang, Jieyang Chen, Xin Liang, Dmitry Ganyushin, Todd Munson, Ian Foster, Jean-Luc Vay, Norbert Podhorszki, Kesheng Wu, Scott Klasky
    http://arxiv.org/abs/2107.07108v1

    • [cs.DC]MXDAG: A Hybrid Abstraction for Cluster Applications
    Weitao Wang, Sushovan Das, Xinyu Crystal Wu, Zhuang Wang, Ang Chen, T. S. Eugene Ng
    http://arxiv.org/abs/2107.07442v1

    • [cs.DC]Scalable Biophysical Simulations of the Neuromuscular System
    Benjamin Maier
    http://arxiv.org/abs/2107.07104v1

    • [cs.GT]DiRe Committee : Diversity and Representation Constraints in Multiwinner Elections
    Kunal Relia
    http://arxiv.org/abs/2107.07356v1

    • [cs.GT]Optimal Scoring Rule Design
    Yiling Chen, Fang-Yi Yu
    http://arxiv.org/abs/2107.07420v1

    • [cs.GT]Two-Sided Matching Meets Fair Division
    Rupert Freeman, Evi Micha, Nisarg Shah
    http://arxiv.org/abs/2107.07404v1

    • [cs.HC]Identifying Competition and Mutualism Between Online Groups
    Nathan TeBlunthuis, Benjamin Mako Hill
    http://arxiv.org/abs/2107.06970v1

    • [cs.IR]Auto-detecting groups based on textual similarity for group recommendations
    Chintoo Kumar, C. Ravindranath Chowdary
    http://arxiv.org/abs/2107.07284v1

    • [cs.IR]Next-item Recommendations in Short Sessions
    Wenzhuo Song, Shoujin Wang, Yan Wang, Shengsheng Wang
    http://arxiv.org/abs/2107.07453v1

    • [cs.IR]Online Learning for Recommendations at Grubhub
    Alex Egg
    http://arxiv.org/abs/2107.07106v1

    • [cs.IR]Recommending best course of treatment based on similarities of prognostic markers\thanks{All authors contributed equally
    Sudhanshu, Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal
    http://arxiv.org/abs/2107.07500v1

    • [cs.IR]Scene-adaptive Knowledge Distillation for Sequential Recommendation via Differentiable Architecture Search
    Lei Chen, Fajie Yuan, Jiaxi Yang, Min Yang, Chengming Li
    http://arxiv.org/abs/2107.07173v1

    • [cs.IT]今日学术视野(2021.7.17) - 图3-Norm Minimization for Joint Precoding and Peak-to-Average-Power Ratio Reduction
    Sueda Taner, Christoph Studer
    http://arxiv.org/abs/2107.06986v1

    • [cs.IT]A Bayesian Compressive Sensing Approach to Robust Near-Field Antenna Characterization
    Marco Salucci, Nicola Anselmi, Marco Donald Migliore, Andrea Massa
    http://arxiv.org/abs/2107.07011v1

    • [cs.IT]Computing Permanents on a Trellis
    Han Mao Kiah, Alexander Vardy, Hanwen Yao
    http://arxiv.org/abs/2107.07377v1

    • [cs.IT]Data Disclosure with Non-zero Leakage and Non-invertible Leakage Matrix
    Amirreza Zamani, Tobias J. Oechtering, Mikael Skoglund
    http://arxiv.org/abs/2107.07484v1

    • [cs.IT]Frequency-Time Division based Deep Learning for OFDM Channel Estimation
    Ang Yang, Peng Sun, Tamrakar Rakesh, Bule Sun, Fei Qin
    http://arxiv.org/abs/2107.07161v1

    • [cs.IT]Joint CFO, Gridless Channel Estimation and Data Detection for Underwater Acoustic OFDM Systems
    Lei Wan, Jiang Zhu, En Cheng, Zhiwei Xu
    http://arxiv.org/abs/2107.07101v1

    • [cs.IT]Moufang Patterns and Geometry of Information
    Noemie Combe, Yuri I. Manin, Matilde Marcolli
    http://arxiv.org/abs/2107.07486v1

    • [cs.IT]On Hard and Soft Decision Decoding of BCH Codes
    Martin Bossert, Rebekka Schulz, Sebastian Bitzer
    http://arxiv.org/abs/2107.07401v1

    • [cs.IT]Support Constrained Generator Matrices and the Generalized Hamming Weights
    Hao Chen
    http://arxiv.org/abs/2107.07093v1

    • [cs.IT]The Feedback Capacity of Noisy Output is the STate (NOST) Channels
    Eli Shemuel, Oron Sabag, Haim Permuter
    http://arxiv.org/abs/2107.07164v1

    • [cs.IT]Trade-Based LDPC Codes
    Farzane Amirzade, Daniel Panario, Mohammad-Reza Sadeghi
    http://arxiv.org/abs/2107.07466v1

    • [cs.IT]Twisted Reed-Solomon Codes
    Peter Beelen, Sven Puchinger, Johan Rosenkilde
    http://arxiv.org/abs/2107.06945v1

    • [cs.LG]A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
    Anastasios N. Angelopoulos, Stephen Bates
    http://arxiv.org/abs/2107.07511v1

    • [cs.LG]A Reinforcement Learning Environment for Mathematical Reasoning via Program Synthesis
    Joseph Palermo, Johnny Ye, Alok Singh
    http://arxiv.org/abs/2107.07373v1

    • [cs.LG]A Robust Deep Learning Workflow to Predict Multiphase Flow Behavior during Geological CO2 Sequestration Injection and Post-Injection Periods
    Bicheng Yan, Bailian Chen, Dylan Robert Harp, Rajesh J. Pawar
    http://arxiv.org/abs/2107.07274v1

    • [cs.LG]A multi-schematic classifier-independent oversampling approach for imbalanced datasets
    Saptarshi Bej, Kristian Schultz, Prashant Srivastava, Markus Wolfien, Olaf Wolkenhauer
    http://arxiv.org/abs/2107.07349v1

    • [cs.LG]Adaptable Agent Populations via a Generative Model of Policies
    Kenneth Derek, Phillip Isola
    http://arxiv.org/abs/2107.07506v1

    • [cs.LG]Algorithmic Concept-based Explainable Reasoning
    Dobrik Georgiev, Pietro Barbiero, Dmitry Kazhdan, Petar Veličković, Pietro Liò
    http://arxiv.org/abs/2107.07493v1

    • [cs.LG]Copula-Based Normalizing Flows
    Mike Laszkiewicz, Johannes Lederer, Asja Fischer
    http://arxiv.org/abs/2107.07352v1

    • [cs.LG]Data vs classifiers, who wins?
    Lucas F. F. Cardoso, Vitor C. A. Santos, Regiane S. Kawasaki Francês, Ricardo B. C. Prudêncio, Ronnie C. O. Alves
    http://arxiv.org/abs/2107.07451v1

    • [cs.LG]DeFed: A Principled Decentralized and Privacy-Preserving Federated Learning Algorithm
    Ye Yuan, Ruijuan Chen, Chuan Sun, Maolin Wang, Feng Hua, Xinlei Yi, Tao Yang, Jun Liu
    http://arxiv.org/abs/2107.07171v1

    • [cs.LG]Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo
    Vyacheslav Kungurtsev, Adam Cobb, Tara Javidi, Brian Jalaian
    http://arxiv.org/abs/2107.07211v1

    • [cs.LG]Expert Graphs: Synthesizing New Expertise via Collaboration
    Bijan Mazaheri, Siddharth Jain, Jehoshua Bruck
    http://arxiv.org/abs/2107.07054v1

    • [cs.LG]Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests
    Sean Kulinski, Saurabh Bagchi, David I. Inouye
    http://arxiv.org/abs/2107.06929v1

    • [cs.LG]Hierarchical graph neural nets can capture long-range interactions
    Ladislav Rampášek, Guy Wolf
    http://arxiv.org/abs/2107.07432v1

    • [cs.LG]Hybrid Bayesian Neural Networks with Functional Probabilistic Layers
    Daniel T. Chang
    http://arxiv.org/abs/2107.07014v1

    • [cs.LG]Input Dependent Sparse Gaussian Processes
    Bahram Jafrasteh, Carlos Villacampa-Calvo, Daniel Hernández-Lobato
    http://arxiv.org/abs/2107.07281v1

    • [cs.LG]Kernel Continual Learning
    Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao, Cees G. M. Snoek
    http://arxiv.org/abs/2107.05757v2

    • [cs.LG]Lockout: Sparse Regularization of Neural Networks
    Gilmer Valdes, Wilmer Arbelo, Yannet Interian, Jerome H. Friedman
    http://arxiv.org/abs/2107.07160v1

    • [cs.LG]MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators
    Jinyoung Choi, Bohyung Han
    http://arxiv.org/abs/2107.07260v1

    • [cs.LG]MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning
    Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr Pong, Aurick Zhou, Justin Yu, Sergey Levine
    http://arxiv.org/abs/2107.07184v1

    • [cs.LG]MultiBench: Multiscale Benchmarks for Multimodal Representation Learning
    Paul Pu Liang, Yiwei Lyu, Xiang Fan, Zetian Wu, Yun Cheng, Jason Wu, Leslie Chen, Peter Wu, Michelle A. Lee, Yuke Zhu, Ruslan Salakhutdinov, Louis-Philippe Morency
    http://arxiv.org/abs/2107.07502v1

    • [cs.LG]NeuSaver: Neural Adaptive Power Consumption Optimization for Mobile Video Streaming
    Kyoungjun Park, Myungchul Kim, Laihyuk Park
    http://arxiv.org/abs/2107.07127v1

    • [cs.LG]On the expressivity of bi-Lipschitz normalizing flows
    Alexandre Verine, Benjamin Negrevergne, Fabrice Rossi, Yann Chevaleyre
    http://arxiv.org/abs/2107.07232v1

    • [cs.LG]Only Train Once: A One-Shot Neural Network Training And Pruning Framework
    Tianyi Chen, Bo Ji, Tianyu Ding, Biyi Fang, Guanyi Wang, Zhihui Zhu, Luming Liang, Yixin Shi, Sheng Yi, Xiao Tu
    http://arxiv.org/abs/2107.07467v1

    • [cs.LG]PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration
    Yuda Song, Wen Sun
    http://arxiv.org/abs/2107.07410v1

    • [cs.LG]Randomized ReLU Activation for Uncertainty Estimation of Deep Neural Networks
    Yufeng Xia, Jun Zhang, Zhiqiang Gong, Tingsong Jiang, Wen Yao
    http://arxiv.org/abs/2107.07197v1

    • [cs.LG]Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks
    Andrey Malinin, Neil Band, German Chesnokov, Yarin Gal, Mark J. F. Gales, Alexey Noskov, Andrey Ploskonosov, Liudmila Prokhorenkova, Ivan Provilkov, Vatsal Raina, Vyas Raina, Mariya Shmatova, Panos Tigas, Boris Yangel
    http://arxiv.org/abs/2107.07455v1

    • [cs.LG]Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box setting
    Xiangyu Qi, Jifeng Zhu, Chulin Xie, Yong Yang
    http://arxiv.org/abs/2107.07240v1

    • [cs.LG]USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems
    Guangmo Tong
    http://arxiv.org/abs/2107.07508v1

    • [cs.LG]You Do Not Need a Bigger Boat: Recommendations at Reasonable Scale in a (Mostly) Serverless and Open Stack
    Jacopo Tagliabue
    http://arxiv.org/abs/2107.07346v1

    • [cs.LO]Proceedings of the Sixteenth Workshop on Logical Frameworks and Meta-Languages: Theory and Practice
    Elaine Pimentel, Enrico Tassi
    http://arxiv.org/abs/2107.07376v1

    • [cs.MA]Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
    Joel Z. Leibo, Edgar Duéñez-Guzmán, Alexander Sasha Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charles Beattie, Igor Mordatch, Thore Graepel
    http://arxiv.org/abs/2107.06857v1

    • [cs.MM]Cross-modal Variational Auto-encoder for Content-based Micro-video Background Music Recommendation
    Jing Yi, Yaochen Zhu, Jiayi Xie, Zhenzhong Chen
    http://arxiv.org/abs/2107.07268v1

    • [cs.NE]Motor Imagery Classification based on CNN-GRU Network with Spatio-Temporal Feature Representation
    Ji-Seon Bang, Seong-Whan Lee
    http://arxiv.org/abs/2107.07062v1

    • [cs.NE]Neural Architecture Search using Covariance Matrix Adaptation Evolution Strategy
    Nilotpal Sinha, Kuan-Wen Chen
    http://arxiv.org/abs/2107.07266v1

    • [cs.NE]Preference Incorporation into Many-Objective Optimization: An Outranking-based Ant Colony Algorithm
    Gilberto Rivera, Carlos A. Coello Coello, Laura Cruz-Reyes, Eduardo R. Fernandez, Claudia Gomez-Santillan, Nelson Rangel-Valdez
    http://arxiv.org/abs/2107.07121v1

    • [cs.NE]Transformer-based Machine Learning for Fast SAT Solvers and Logic Synthesis
    Feng Shi, Chonghan Lee, Mohammad Khairul Bashar, Nikhil Shukla, Song-Chun Zhu, Vijaykrishnan Narayanan
    http://arxiv.org/abs/2107.07116v1

    • [cs.RO]A Low-Complexity Radar Detector Outperforming OS-CFAR for Indoor Drone Obstacle Avoidance
    Ali Safa, Tim Verbelen, Lars Keuninckx, Ilja Ocket, Matthias Hartmann, André Bourdoux, Franky Catthoor, Georges Gielen
    http://arxiv.org/abs/2107.07250v1

    • [cs.RO]A life-long SLAM approach using adaptable local maps based on rasterized LIDAR images
    Waqas Ali, Peilin Liu, Rendong Ying, Zheng Gong
    http://arxiv.org/abs/2107.07133v1

    • [cs.RO]An End-to-End Differentiable Framework for Contact-Aware Robot Design
    Jie Xu, Tao Chen, Lara Zlokapa, Michael Foshey, Wojciech Matusik, Shinjiro Sueda, Pulkit Agrawal
    http://arxiv.org/abs/2107.07501v1

    • [cs.RO]Collision Avoidance Using Spherical Harmonics
    Steven Patrick, Efstathios Bakolas
    http://arxiv.org/abs/2107.07117v1

    • [cs.RO]Conflict-free Cooperation Method for Connected and Automated Vehicles at Unsignalized Intersections: Graph-based Modeling and Optimality Analysis
    Chaoyi Chen, Qing Xu, Mengchi Cai, Jiawei Wang, Jianqiang Wang, Biao Xu, Keqiang Li
    http://arxiv.org/abs/2107.07179v1

    • [cs.RO]Deformable Ela
    5892
    sto-Plastic Object Shaping using an Elastic Hand and Model-Based Reinforcement Learning
    Carolyn Matl, Ruzena Bajcsy
    http://arxiv.org/abs/2107.06924v1

    • [cs.RO]Design of Distributed Reconfigurable Robotics Systems with ReconROS
    Christian Lienen, Marco Platzner
    http://arxiv.org/abs/2107.07208v1

    • [cs.RO]GI-NNet & RGI-NNet: Development of Robotic Grasp Pose Models, Trainable with Large as well as Limited Labelled Training Datasets, under supervised and semi supervised paradigms
    Priya Shukla, Nilotpal Pramanik, Deepesh Mehta, G. C. Nandi
    http://arxiv.org/abs/2107.07452v1

    • [cs.RO]High-level Decisions from a Safe Maneuver Catalog with Reinforcement Learning for Safe and Cooperative Automated Merging
    Danial Kamran, Yu Ren, Martin Lauer
    http://arxiv.org/abs/2107.07413v1

    • [cs.RO]Learning Sparse Interaction Graphs of Partially Observed Pedestrians for Trajectory Prediction
    Zhe Huang, Ruohua Li, Kazuki Shin, Katherine Driggs-Campbell
    http://arxiv.org/abs/2107.07056v1

    • [cs.RO]Minimizing Safety Interference for Safe an
    a07
    d Comfortable Automated Driving with Distributional Reinforcement Learning
    Danial Kamran, Tizian Engelgeh, Marvin Busch, Johannes Fischer, Christoph Stiller
    http://arxiv.org/abs/2107.07316v1

    • [cs.RO]On nondeterminism in combinatorial filters
    Yulin Zhang, Dylan A. Shell
    http://arxiv.org/abs/2107.07111v1

    • [cs.RO]OpenCDA:An Open Cooperative Driving Automation Framework Integrated with Co-Simulation
    Runsheng Xu, Yi Guo, Xu Han, Xin Xia, Hao Xiang, Jiaqi Ma
    http://arxiv.org/abs/2107.06260v2

    • [cs.RO]Optimization-Based Quadrupedal Hybrid Wheeled-Legged Locomotion
    Italo Belli, Matteo Parigi Polverini, Arturo Laurenzi, Enrico Mingo Hoffman, Paolo Rocco, Nikolaos Tsagarakis
    http://arxiv.org/abs/2107.07507v1

    • [cs.RO]Personalizing User Engagement Dynamics in a Non-Verbal Communication Game for Cerebral Palsy
    Nathaniel Dennler, Catherine Yunis, Jonathan Realmuto, Terence Sanger, Stefanos Nikolaidis, Maja Matarić
    http://arxiv.org/abs/2107.07446v1

    • [cs.RO]Real-Time Grasping Strategies Using Event Camera
    Xiaoqian Huang, Mohamad Halwani, Rajkumar Muthusamy, Abdulla Ayyad, Dewald Swart, Lakmal Seneviratne, Dongming Gan, Yahya Zweiri
    http://arxiv.org/abs/2107.07200v1

    • [cs.RO]Rule-based Evaluation and Optimal Control for Autonomous Driving
    Wei Xiao, Noushin Mehdipour, Anne Collin, Amitai Y. Bin-Nun, Emilio Frazzoli, Radboud Duintjer Tebbens, Calin Belta
    http://arxiv.org/abs/2107.07460v1

    • [cs.RO]Sensorimotor-inspired Tactile Feedback and Control Improve Consistency of Prosthesis Manipulation in the Absence of Direct Vision
    Neha Thomas, Farimah Fazlollahi, Jeremy D. Brown, Katherine J. Kuchenbecker
    http://arxiv.org/abs/2107.07000v1

    • [cs.RO]VILENS: Visual, Inertial, Lidar, and Leg Odometry for All-Terrain Legged Robots
    David Wisth, Marco Camurri, Maurice Fallon
    http://arxiv.org/abs/2107.07243v1

    • [cs.RO]Vision-Based Target Localization for a Flapping-Wing Aerial Vehicle
    Xinghao Dong, Qiang Fu, Chunhua Zhang, Wei He
    http://arxiv.org/abs/2107.07084v1

    • [cs.SE]Empowered and Embedded: Ethics and Agile Processes
    Niina Zuber, Severin Kacianka, Jan Gogoll, Alexander Pretschner, Julian Nida-Rümelin
    http://arxiv.org/abs/2107.07249v1

    • [cs.SE]Neural Code Summarization: How Far Are We?
    Ensheng Shi, Yanlin Wang, Lun Du, Junjie Chen, Shi Han, Hongyu Zhang, Dongmei Zhang, Hongbin Sun
    http://arxiv.org/abs/2107.07112v1

    • [cs.SE]Reel Life vs. Real Life: How Software Developers Share Their Daily Life through Vlogs
    Souti Chattopadhyay, Thomas Zimmermann, Denae Ford
    http://arxiv.org/abs/2107.07023v1

    • [cs.SI]Clustering of heterogeneous populations of networks
    Jean-Gabriel Young, Alec Kirkley, M. E. J. Newman
    http://arxiv.org/abs/2107.07489v1

    • [cs.SI]Look who’s watching: platform labels and user engagement on state-backed media outlets
    Samantha Bradshaw, Mona Elswah, Antonella Perini
    http://arxiv.org/abs/2107.06978v1

    • [cs.SI]Should I Stay or Should I Go: Predicting Changes in Cluster Membership
    Evangelia Tsoukanara, Georgia Koloniari, Evaggelia Pitoura
    http://arxiv.org/abs/2107.07362v1

    • [econ.EM]Generalized Covariance Estimator
    Christian Gourieroux, Joann Jasiak
    http://arxiv.org/abs/2107.06979v1

    • [eess.AS]VAD-free Streaming Hybrid CTC/Attention ASR for Unsegmented Recording
    Hirofumi Inaguma, Tatsuya Kawahara
    http://arxiv.org/abs/2107.07509v1

    • [eess.IV]A modular U-Net for automated segmentation of X-ray tomography images in composite materials
    João P C Bertoldo, Etienne Decencière, David Ryckelynck, Henry Proudhon
    http://arxiv.org/abs/2107.07468v1

    • [eess.IV]End-to-end Ultrasound Frame to Volume Registration
    Hengtao Guo, Xuanang Xu, Sheng Xu, Bradford J. Wood, Pingkun Yan
    http://arxiv.org/abs/2107.06449v1

    • [eess.IV]Multi-Channel Auto-Encoders and a Novel Dataset for Learning Domain Invariant Representations of Histopathology Images
    Andrew Moyes, Richard Gault, Kun Zhang, Ji Ming, Danny Crookes, Jing Wang
    http://arxiv.org/abs/2107.07271v1

    • [eess.IV]RCDNet: An Interpretable Rain Convolutional Dictionary Network for Single Image Deraining
    Hong Wang, Qi Xie, Qian Zhao, Yong Liang, Deyu Meng
    http://arxiv.org/abs/2107.06808v1

    • [eess.SP]Frequency-packed Faster-than-Nyquist Signaling via Symbol-level Precoding for Multi-user MISO Redundant Transmissions
    Wallace A. Martins, Symeon Chatzinotas, Björn Ottersten
    http://arxiv.org/abs/2107.06962v1

    • [eess.SP]Multiclass Permanent Magnets Superstructure for Indoor Localization using Artificial Intelligence
    Amir Ivry, Elad Fisher, Roger Alimi, Idan Mosseri, Kanna Nahir
    http://arxiv.org/abs/2107.07425v1

    • [eess.SP]Optimality of the Discrete Fourier Transform for Beamspace Massive MU-MIMO Communication
    Sueda Taner, Christoph Studer
    http://arxiv.org/abs/2107.06953v1

    • [math.OC]Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update
    Michał Dereziński, Jonathan Lacotte, Mert Pilanci, Michael W. Mahoney
    http://arxiv.org/abs/2107.07480v1

    • [math.PR]Determinantal Point Processes in the Flat Limit
    Simon Barthelmé, Nicolas Tremblay, Konstantin Usevich, Pierre-Olivier Amblard
    http://arxiv.org/abs/2107.07213v1

    • [math.PR]Performance of Bayesian linear regression in a model with mismatch
    Jean Barbier, Wei-Kuo Chen, Dmitry Panchenko, Manuel Sáenz
    http://arxiv.org/abs/2107.06936v1

    • [math.ST]On the early solution path of best subset selection
    Ziwei Zhu, Shihao Wu
    http://arxiv.org/abs/2107.06939v1

    • [math.ST]The Completion of Covariance Kernels
    Kartik G. Waghmare, Victor M. Panaretos
    http://arxiv.org/abs/2107.07350v1

    • [math.ST]The Information Projection in Moment Inequality Models: Existence, Dual Representation, and Approximation
    Rami V. Tabri
    http://arxiv.org/abs/2107.07140v1

    • [physics.flu-dyn]Predicting the near-wall region of turbulence through convolutional neural networks
    A. G. Balasubramanian, L. Guastoni, A. Güemes, A. Ianiro, S. Discetti, P. Schlatter, H. Azizpour, R. Vinuesa
    http://arxiv.org/abs/2107.07340v1

    • [physics.soc-ph]Deep learning based parameter search for an agent based social network model
    Yohsuke Murase, Hang-Hyun Jo, János Török, János Kertész, Kimmo Kaski
    http://arxiv.org/abs/2107.06507v1

    • [physics.soc-ph]From Reddit to Wall Street: The role of committed minorities in financial collective action
    Lorenzo Lucchini, Luca Maria Aiello, Laura Alessandretti, Gianmarco De Francisci Morales, Michele Starnini, Andrea Baronchelli
    http://arxiv.org/abs/2107.07361v1

    • [q-fin.ST]Credit scoring using neural networks and SURE posterior probability calibration
    Matthieu Garcin, Samuel Stéphan
    http://arxiv.org/abs/2107.07206v1

    • [quant-ph]A Combinatorial Interpretation for the Shor-Laflamme Weight Enumerators of CWS Codes
    Andrew Nemec, Andreas Klappenecker
    http://arxiv.org/abs/2107.07071v1

    • [quant-ph]Szegedy Walk Unitaries for Quantum Maps
    Pawel Wocjan, Kristan Temme
    http://arxiv.org/abs/2107.07365v1

    • [stat.AP]Statistical modeling of corneal OCT speckle. A distributional model-free approach
    Marcela Niemczyk, D. Robert Iskander
    http://arxiv.org/abs/2107.07256v1

    • [stat.CO]A comparison of nonlinear extensions to the ensemble Kalman filter: Gaussian Anamorphosis and Two-Step Ensemble Filters
    Ian Grooms
    http://arxiv.org/abs/2107.07475v1

    • [stat.ME]A new class of conditional Markov jump processes with regime switching and path dependence: properties and maximum likelihood estimation
    Budhi Surya
    http://arxiv.org/abs/2107.07026v1

    • [stat.ME]Covariate adjustment in randomised trials: canonical link functions protect against model mis-specification
    Ian R. White, Tim P Morris, Elizabeth Williamson
    http://arxiv.org/abs/2107.07278v1

    • [stat.ME]Estimation of spatially varying parameters with application to hyperbolic SPDEs
    David Angwenyi
    http://arxiv.org/abs/2107.07246v1

    • [stat.ME]Independence weights for causal inference with continuous exposures
    Jared D. Huling, Noah Greifer, Guanhua Chen
    http://arxiv.org/abs/2107.07086v1

    • [stat.ME]Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces
    Xueqin Wang, Jin Zhu, Wenliang Pan, Junhao Zhu, Heping Zhang
    http://arxiv.org/abs/2107.07317v1

    • [stat.ME]Nonparametric, tuning-free estimation of S-shaped functions
    Oliver Y. Feng, Yining Chen, Qiyang Han, Raymond J. Carroll, Richard J. Samworth
    http://arxiv.org/abs/2107.07257v1

    • [stat.ME]Personalized and Reliable Decision Sets: Enhancing Interpretability in Clinical Decision Support Systems
    Francisco Valente, Simão Paredes, Jorge Henriques
    http://arxiv.org/abs/2107.07483v1

    • [stat.ME]Statistical inference using Regularized M-estimation in the reproducing kernel Hilbert space for handling missing data
    Hengfang Wang, Jae Kwang Kim
    http://arxiv.org/abs/2107.07371v1

    • [stat.ME]Temporally Local Maximum Likelihood with Application to SIS Model
    Christian Gourieroux, Joann Jasiak
    http://arxiv.org/abs/2107.06971v1

    • [stat.ME]The Taxicab Sampler: MCMC for Discrete Spaces with Application to Tree Models
    Vincent Geels, Matthew Pratola, Radu Herbei
    http://arxiv.org/abs/2107.07313v1

    • [stat.ML]A unified framework for bandit multiple testing
    Ziyu Xu, Ruodu Wang, Aaditya Ramdas
    http://arxiv.org/abs/2107.07322v1

    • [stat.ML]Entropic Inequality Constraints from 今日学术视野(2021.7.17) - 图4-separation Relations in Directed Acyclic Graphs with Hidden Variables
    Noam Finkelstein, Beata Zjawin, Elie Wolfe, Ilya Shpitser, Robert W. Spekkens
    http://arxiv.org/abs/2107.07087v1

    • [stat.ML]FastSHAP: Real-Time Shapley Value Estimation
    Neil Jethani, Mukund Sudarshan, Ian Covert, Su-In Lee, Rajesh Ranganath
    http://arxiv.org/abs/2107.07436v1

    • [stat.ML]Hida-Matérn Kernel
    Matthew Dowling, Piotr Sokół, Il Memming Park
    http://arxiv.org/abs/2107.07098v1

    • [stat.ML]Mid-flight Forecasting for CPA Lines in Online Advertising
    Hao He, Tian Zhou, Lihua Ren, Niklas Karlsson, Aaron Flores
    http://arxiv.org/abs/2107.07494v1

    • [stat.ML]Multi-label Chaining with Imprecise Probabilities
    Yonatan Carlos Carranza Alarcón, Sébastien Destercke
    http://arxiv.org/abs/2107.07443v1

    • [stat.ML]Principal component analysis for Gaussian process posteriors
    Hideaki Ishibashi, Shotaro Akaho
    http://arxiv.org/abs/2107.07115v1