{"list":"other","total":68,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1706.06083","title":"Towards Deep Learning Models Resistant to Adversarial Attacks","created":"2017-06-19","cited_by_count":6415},{"id":"2203.00667","title":"Generative Adversarial Networks","created":"2022-03-01","cited_by_count":5627},{"id":"1608.04644","title":"Towards Evaluating the Robustness of Neural Networks","created":"2016-08-16","cited_by_count":2998},{"id":"1704.02685","title":"Learning Important Features Through Propagating Activation Differences","created":"2017-04-10","cited_by_count":1458},{"id":"1702.01135","title":"Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks","created":"2017-02-03","cited_by_count":744},{"id":"1803.10892","title":"Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks","created":"2018-03-29","cited_by_count":690},{"id":"1806.07538","title":"Towards Robust Interpretability with Self-Explaining Neural Networks","created":"2018-06-20","cited_by_count":505},{"id":"1902.06705","title":"On Evaluating Adversarial Robustness","created":"2019-02-18","cited_by_count":447},{"id":"1910.05449","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","created":"2019-10-12","cited_by_count":420},{"id":"2103.14023","title":"AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting","created":"2021-03-25","cited_by_count":331},{"id":"2002.11927","title":"Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction","created":"2020-02-27","cited_by_count":325},{"id":"1704.04394","title":"DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents","created":"2017-04-14","cited_by_count":310},{"id":"1806.01482","title":"SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints","created":"2018-06-05","cited_by_count":298},{"id":"1703.08603","title":"Adversarial Examples for Semantic Segmentation and Object Detection","created":"2017-03-24","cited_by_count":275},{"id":"1911.10298","title":"CoverNet: Multimodal Behavior Prediction using Trajectory Sets","created":"2019-11-23","cited_by_count":259},{"id":"1801.02610","title":"Generating Adversarial Examples with Adversarial Networks","created":"2018-01-08","cited_by_count":258},{"id":"2004.02025","title":"It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction","created":"2020-04-04","cited_by_count":236},{"id":"1907.03395","title":"Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks","created":"2019-07-04","cited_by_count":229},{"id":"2012.02046","title":"Neural Prototype Trees for Interpretable Fine-grained Image Recognition","created":"2020-12-03","cited_by_count":214},{"id":"1710.04689","title":"Social Attention: Modeling Attention in Human Crowds","created":"2017-10-12","cited_by_count":186},{"id":"2203.13777","title":"Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion","created":"2022-03-25","cited_by_count":185},{"id":"1911.00997","title":"Multiple Futures Prediction","created":"2019-11-04","cited_by_count":178},{"id":"1603.08507","title":"Generating Visual Explanations","created":"2016-03-28","cited_by_count":158},{"id":"1809.07016","title":"Generating 3D Adversarial Point Clouds","created":"2018-09-19","cited_by_count":144},{"id":"1904.04776","title":"Multi-Agent Tensor Fusion for Contextual Trajectory Prediction","created":"2019-04-09","cited_by_count":131},{"id":"2004.05519","title":"NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems","created":"2020-04-12","cited_by_count":128},{"id":"2204.08770","title":"GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction with Relational Reasoning","created":"2022-04-19","cited_by_count":128},{"id":"2104.01528","title":"SGCN:Sparse Graph Convolution Network for Pedestrian Trajectory Prediction","created":"2021-04-04","cited_by_count":97},{"id":"1909.04326","title":"Universal Physical Camouflage Attacks on Object Detectors","created":"2019-09-10","cited_by_count":91},{"id":"2201.05057","title":"On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles","created":"2022-01-13","cited_by_count":90},{"id":"2203.11474","title":"Remember Intentions: Retrospective-Memory-based Trajectory Prediction","created":"2022-03-22","cited_by_count":86},{"id":"1912.00461","title":"AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds","created":"2019-12-01","cited_by_count":84},{"id":"2004.12255","title":"TPNet: Trajectory Proposal Network for Motion Prediction","created":"2020-04-26","cited_by_count":80},{"id":"1904.09507","title":"Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs","created":"2019-04-20","cited_by_count":79},{"id":"1905.01631","title":"Conditional Generative Neural System for Probabilistic Trajectory Prediction","created":"2019-05-05","cited_by_count":76},{"id":"2111.14338","title":"Improving Deep Learning Interpretability by Saliency Guided Training","created":"2021-11-29","cited_by_count":68},{"id":"2004.05682","title":"PatchAttack: A Black-box Texture-based Attack with Reinforcement Learning","created":"2020-04-12","cited_by_count":67},{"id":"2108.09274","title":"MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction","created":"2021-08-20","cited_by_count":61},{"id":"2012.11717","title":"Social NCE: Contrastive Learning of Socially-aware Motion Representations","created":"2020-12-21","cited_by_count":58},{"id":"1906.10395","title":"Quantitative Verification of Neural Networks And its Security Applications","created":"2019-06-25","cited_by_count":56},{"id":"1811.07209","title":"A Statistical Approach to Assessing Neural Network Robustness","created":"2018-11-17","cited_by_count":54},{"id":"2012.03058","title":"BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations","created":"2020-12-05","cited_by_count":51},{"id":"1811.12395","title":"CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks","created":"2018-11-29","cited_by_count":50},{"id":"2209.08744","title":"AdvDO: Realistic Adversarial Attacks for Trajectory Prediction","created":"2022-09-19","cited_by_count":49},{"id":"2103.07854","title":"Three Steps to Multimodal Trajectory Prediction: Modality Clustering, Classification and Synthesis","created":"2021-03-14","cited_by_count":46},{"id":"2203.13471","title":"Non-Probability Sampling Network for Stochastic Human Trajectory Prediction","created":"2022-03-25","cited_by_count":46},{"id":"2004.10281","title":"Probabilistic Safety for Bayesian Neural Networks","created":"2020-04-21","cited_by_count":42},{"id":"2203.06020","title":"Enhancing Adversarial Training with Second-Order Statistics of Weights","created":"2022-03-11","cited_by_count":42},{"id":"1902.05983","title":"Robustness of Neural Networks: A Probabilistic and Practical Approach","created":"2019-02-15","cited_by_count":38},{"id":"2206.05712","title":"Graph-based Spatial Transformer with Memory Replay for Multi-future Pedestrian Trajectory Prediction","created":"2022-06-12","cited_by_count":36},{"id":"1903.01980","title":"Statistical Guarantees for the Robustness of Bayesian Neural Networks","created":"2019-03-05","cited_by_count":35},{"id":"2002.06864","title":"Scalable Quantitative Verification For Deep Neural Networks","created":"2020-02-17","cited_by_count":31},{"id":"2010.07722","title":"Improving Neural Network Verification through Spurious Region Guided Refinement","created":"2020-10-15","cited_by_count":31},{"id":"2004.04340","title":"Reciprocal Learning Networks for Human Trajectory Prediction","created":"2020-04-09","cited_by_count":30},{"id":"2107.14204","title":"Personalized Trajectory Prediction via Distribution Discrimination","created":"2021-07-29","cited_by_count":30},{"id":"2003.08907","title":"Overinterpretation reveals image classification model pathologies","created":"2020-03-19","cited_by_count":28},{"id":"2208.09418","title":"SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability","created":"2022-08-19","cited_by_count":28},{"id":"2303.10653","title":"Randomized Adversarial Training via Taylor Expansion","created":"2023-03-19","cited_by_count":28},{"id":"2010.09345","title":"A Framework to Learn with Interpretation","created":"2020-10-19","cited_by_count":23},{"id":"2208.00094","title":"Robust Trajectory Prediction against Adversarial Attacks","created":"2022-07-29","cited_by_count":17},{"id":"1812.07667","title":"GD-GAN: Generative Adversarial Networks for Trajectory Prediction and Group Detection in Crowds","created":"2018-12-18","cited_by_count":15},{"id":"2010.16267","title":"Exploring Dynamic Context for Multi-path Trajectory Prediction","created":"2020-10-30","cited_by_count":14},{"id":"2101.10102","title":"Towards Practical Robustness Analysis for DNNs based on PAC-Model Learning","created":"2021-01-25","cited_by_count":12},{"id":"2205.14230","title":"Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction","created":"2022-05-27","cited_by_count":12},{"id":"2212.04138","title":"Targeted Adversarial Attacks against Neural Network Trajectory Predictors","created":"2022-12-08","cited_by_count":11},{"id":"2007.10141","title":"PAC Model Checking of Black-Box Continuous-Time Dynamical Systems","created":"2020-07-17","cited_by_count":8},{"id":"2108.06384","title":"Finding Representative Interpretations on Convolutional Neural Networks","created":"2021-08-13","cited_by_count":3}],"next_cursor":null}