Tags AAAI Stanford AI Lab Papers and Talks at AAAI 2022 February 22, 2022 ACL Stanford AI Lab Papers and Talks at ACL 2022 May 25, 2022 Stanford AI Lab Papers at ACL-IJCNLP 2021 August 2, 2021 Stanford AI Lab Papers and Talks at ACL 2020 July 6, 2020 ACL-IJCNLP Stanford AI Lab Papers at ACL-IJCNLP 2021 August 2, 2021 AI Salon AI and the Future of Work December 20, 2018 Deep Learning, Structure and Innate Priors December 3, 2018 AI for policy Supporting COVID-19 policy response with large-scale mobility-based modeling August 16, 2021 AISTATS Stanford AI Lab Papers and Talks at AISTATS 2021 April 13, 2021 About About May 4, 2023 Subscribe May 4, 2023 Archive About May 4, 2023 Subscribe May 4, 2023 COVID-19 Supporting COVID-19 policy response with large-scale mobility-based modeling August 16, 2021 CVPR Stanford AI Lab Papers and Talks at CVPR 2022 June 21, 2022 AGQA: A Benchmark for Compositional, Spatio-Temporal Reasoning June 21, 2021 Stanford AI Lab Papers and Talks at CVPR 2021 June 20, 2021 Stanford AI Lab Papers and Talks at CVPR 2020 June 15, 2020 CoRL Stanford AI Lab Papers and Talks at CoRL 2022 December 16, 2022 Stanford AI Lab Papers at CoRL 2021 November 5, 2021 Stanford AI Lab Papers and Talks at CoRL 2020 November 16, 2020 Data Integration An Introduction to Knowledge Graphs May 10, 2021 ECCV Stanford AI Lab Papers and Talks at ECCV 2022 October 25, 2022 Stanford AI Lab Papers and Talks at ECCV 2020 August 23, 2020 EMNLP Stanford AI Lab Papers and Talks at EMNLP 2022 December 3, 2022 Stanford AI Lab Papers at EMNLP/CoNLL 2021 November 5, 2021 Stanford AI Lab Papers and Talks at EMNLP 2020 November 15, 2020 Healthcare Towards Vision-Based Smart Hospitals November 19, 2018 ICCV Stanford AI Lab Papers at ICCV 2021 October 8, 2021 ICLR Stanford AI Lab Papers and Talks at ICLR 2023 May 1, 2023 Stanford AI Lab Papers and Talks at ICML 2022 July 18, 2022 Stanford AI Lab Papers and Talks at NAACL 2022 July 10, 2022 Stanford AI Lab Papers and Talks at ICLR 2022 April 25, 2022 Stanford AI Lab Papers and Talks at ICLR 2021 May 3, 2021 Conventions in Multi-Agent Collaboration April 28, 2021 Stanford AI Lab Papers and Talks at ICML 2020 July 11, 2020 SAIL and Stanford Robotics at ICRA 2020 May 30, 2020 SAIL at ICLR 2020: Accepted Papers and Videos April 27, 2020 ICML WILDS: A Benchmark of in-the-Wild Distribution Shifts July 19, 2021 Stanford AI Lab Papers and Talks at ICML 2021 July 17, 2021 ICRA Stanford AI Lab Robotics Papers (ICRA and RSS 2022) June 20, 2022 IROS Stanford AI Lab Papers and Talks at IROS 2022 October 25, 2022 KDD 2021 Supporting COVID-19 policy response with large-scale mobility-based modeling August 16, 2021 Knowledge Representation An Introduction to Knowledge Graphs May 10, 2021 MDP Grading Complex Interactive Coding Programs with Reinforcement Learning March 28, 2022 ML Blue People v. City of Ney December 20, 2020 Meta Hello World2 November 18, 2018 NED Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation November 12, 2020 NLP Stanford AI Lab Papers and Talks at ACL 2022 May 25, 2022 An Introduction to Knowledge Graphs May 10, 2021 NeurIPS Stanford AI Lab Papers and Talks at NeurIPS 2022 November 30, 2022 Stanford AI Lab Papers and Talks at NeurIPS 2021 December 6, 2021 Stanford AI Lab Papers and Talks at NeurIPS 2020 December 6, 2020 PAC Towards Vision-Based Smart Hospitals November 19, 2018 RSS Stanford AI Lab Robotics Papers (ICRA and RSS 2022) June 20, 2022 Stanford Papers and Workshops at RSS 2020 July 9, 2020 SGD Neural Mechanics: Symmetry and Broken Conservation Laws In Deep Learning Dynamics February 25, 2021 Search An Introduction to Knowledge Graphs May 10, 2021 VQA AGQA: A Benchmark for Compositional, Spatio-Temporal Reasoning June 21, 2021 Vision An Introduction to Knowledge Graphs May 10, 2021 ai From Discrimination in Machine Learning to Discrimination in Law, Part 2: Disparate Impact December 23, 2022 From Discrimination in Machine Learning to Discrimination in Law, Part 1: Disparate Treatment December 5, 2022 Learning to Imitate November 1, 2022 Can Longer Sequences Help Take the Next Leap in AI? June 9, 2022 Answering Complex Open-domain Questions at Scale October 21, 2019 What makes a good conversation? August 18, 2019 Towards an Educational Revolution Through Chatbots July 12, 2019 alexa prize Inside Chirpy Cardinal: Stanford's Open-Source Social Chatbot that Won 2nd place in the Alexa Prize April 9, 2021 analysis Do Language Models Know How Heavy an Elephant Is? February 17, 2021 artificial intelligence Can Longer Sequences Help Take the Next Leap in AI? June 9, 2022 assistance Controlling Assistive Robots with Learned Latent Actions November 11, 2019 automatic feedback Grading Complex Interactive Coding Programs with Reinforcement Learning March 28, 2022 Meta-Learning Student Feedback to 16,000 Solutions July 20, 2021 autonomous driving Safety Validation of Black-Box Autonomous Systems August 31, 2020 Back to the Future: Planning-Aware Trajectory Forecasting for Autonomous Driving June 25, 2020 autonomy Batch-Active Preference-Based Learning of Reward Functions December 10, 2018 Altruistic Autonomy: Beating Congestion on Shared Roads November 26, 2018 baleen Building Scalable, Explainable, and Adaptive NLP Models with Retrieval October 5, 2021 bayesian inference How does in-context learning work? A framework for understanding the differences from traditional supervised learning August 1, 2022 bert LinkBERT: Improving Language Model Training with Document Link May 31, 2022 Do Language Models Know How Heavy an Elephant Is? February 17, 2021 BERT, ELMo, & GPT-2: How Contextual are Contextualized Word Representations? March 24, 2020 bertology Do Language Models Know How Heavy an Elephant Is? February 17, 2021 bias Measuring Bias in NLP (with Confidence!) November 11, 2020 causal inference Faithful, Interpretable Model Explanations via Causal Abstraction October 31, 2022 Text Feature Selection for Causal Inference December 5, 2019 chatbots Inside Chirpy Cardinal: Stanford's Open-Source Social Chatbot that Won 2nd place in the Alexa Prize April 9, 2021 What makes a good conversation? August 18, 2019 Towards an Educational Revolution Through Chatbots July 12, 2019 clustering BanditPAM: Almost Linear-Time k-medoids Clustering via Multi-Armed Bandits December 17, 2021 code education Grading Complex Interactive Coding Programs with Reinforcement Learning March 28, 2022 Meta-Learning Student Feedback to 16,000 Solutions July 20, 2021 code in place Meta-Learning Student Feedback to 16,000 Solutions July 20, 2021 cognitive modeling When Humans Aren’t Optimal: Robots that Collaborate with Risk-Aware Humans March 17, 2020 colbert Building Scalable, Explainable, and Adaptive NLP Models with Retrieval October 5, 2021 colbert-qa Building Scalable, Explainable, and Adaptive NLP Models with Retrieval October 5, 2021 communication Learning from My Partner’s Actions: Roles in Decentralized Robot Teams October 28, 2019 compositionality AGQA: A Benchmark for Compositional, Spatio-Temporal Reasoning June 21, 2021 compressed sensing Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization April 17, 2019 computational geometry A Topology Layer for Machine Learning August 23, 2019 computational neuroscience A Model-Based Approach Towards Identifying the Brain's Learning Algorithms December 9, 2020 computational topology A Topology Layer for Machine Learning August 23, 2019 computer vision Selective Classification Can Magnify Disparities Across Groups October 13, 2021 Broadening the Reach of Contrastive Learning with Viewmaker Networks April 20, 2021 Learning from Language Explanations November 23, 2020 conference Stanford AI Lab Papers and Talks at ICLR 2023 May 1, 2023 Stanford AI Lab Papers and Talks at CoRL 2022 December 16, 2022 Stanford AI Lab Papers and Talks at EMNLP 2022 December 3, 2022 Stanford AI Lab Papers and Talks at NeurIPS 2022 November 30, 2022 Stanford AI Lab Papers and Talks at IROS 2022 October 25, 2022 Stanford AI Lab Papers and Talks at ECCV 2022 October 25, 2022 Stanford AI Lab Papers and Talks at ICML 2022 July 18, 2022 Stanford AI Lab Papers and Talks at NAACL 2022 July 10, 2022 Stanford AI Lab Papers and Talks at CVPR 2022 June 21, 2022 Stanford AI Lab Robotics Papers (ICRA and RSS 2022) June 20, 2022 Stanford AI Lab Papers and Talks at ACL 2022 May 25, 2022 Stanford AI Lab Papers and Talks at ICLR 2022 April 25, 2022 Stanford AI Lab Papers and Talks at AAAI 2022 February 22, 2022 Stanford AI Lab Papers and Talks at NeurIPS 2021 December 6, 2021 Stanford AI Lab Papers at EMNLP/CoNLL 2021 November 5, 2021 Stanford AI Lab Papers at CoRL 2021 November 5, 2021 Stanford AI Lab Papers at ICCV 2021 October 8, 2021 Stanford AI Lab Papers at ACL-IJCNLP 2021 August 2, 2021 Stanford AI Lab Papers and Talks at ICML 2021 July 17, 2021 AGQA: A Benchmark for Compositional, Spatio-Temporal Reasoning June 21, 2021 Stanford AI Lab Papers and Talks at CVPR 2021 June 20, 2021 Stanford AI Lab Papers and Talks at ICLR 2021 May 3, 2021 Stanford AI Lab Papers and Talks at AISTATS 2021 April 13, 2021 Stanford AI Lab Papers and Talks at NeurIPS 2020 December 6, 2020 Stanford AI Lab Papers and Talks at CoRL 2020 November 16, 2020 Stanford AI Lab Papers and Talks at EMNLP 2020 November 15, 2020 Stanford AI Lab Papers and Talks at ECCV 2020 August 23, 2020 Stanford AI Lab Papers and Talks at ICML 2020 July 11, 2020 Stanford Papers and Workshops at RSS 2020 July 9, 2020 Stanford AI Lab Papers and Talks at ACL 2020 July 6, 2020 Stanford AI Lab Papers and Talks at CVPR 2020 June 15, 2020 SAIL and Stanford Robotics at ICRA 2020 May 30, 2020 SAIL at ICLR 2020: Accepted Papers and Videos April 27, 2020 conservation Neural Mechanics: Symmetry and Broken Conservation Laws In Deep Learning Dynamics February 25, 2021 contrastive learning Broadening the Reach of Contrastive Learning with Viewmaker Networks April 20, 2021 control Learning from My Partner’s Actions: Roles in Decentralized Robot Teams October 28, 2019 Altruistic Autonomy: Beating Congestion on Shared Roads November 26, 2018 creative writing How to Fill in the Blanks with Language Models September 10, 2020 data centric ai Our Journey towards Data-Centric AI: A Retrospective September 15, 2021 deep learning Learning to Imitate November 1, 2022 How does in-context learning work? A framework for understanding the differences from traditional supervised learning August 1, 2022 Understanding Deep Learning Algorithms that Leverage Unlabeled Data, Part 1: Self-training February 24, 2022 Extrapolating to Unnatural Language Processing with GPT-3's In-context Learning: The Good, the Bad, and the Mysterious May 28, 2021 Controllable Fairness in Machine Learning May 27, 2019 Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization April 17, 2019 deep learning theory Neural Mechanics: Symmetry and Broken Conservation Laws In Deep Learning Dynamics February 25, 2021 deep networks A Model-Based Approach Towards Identifying the Brain's Learning Algorithms December 9, 2020 demonstration Batch-Active Preference-Based Learning of Reward Functions December 10, 2018 demonstrations Influencing Leading and Following in Human-Robot Teams June 24, 2019 Learning Reward Functions by Integrating Human Demonstrations and Preferences June 22, 2019 discrimination From Discrimination in Machine Learning to Discrimination in Law, Part 2: Disparate Impact December 23, 2022 From Discrimination in Machine Learning to Discrimination in Law, Part 1: Disparate Treatment December 5, 2022 disparate impact From Discrimination in Machine Learning to Discrimination in Law, Part 2: Disparate Impact December 23, 2022 disparate treatment From Discrimination in Machine Learning to Discrimination in Law, Part 1: Disparate Treatment December 5, 2022 distribution shift Selective Classification Can Magnify Disparities Across Groups October 13, 2021 WILDS: A Benchmark of in-the-Wild Distribution Shifts July 19, 2021 domain generalization WILDS: A Benchmark of in-the-Wild Distribution Shifts July 19, 2021 domain-agnostic Broadening the Reach of Contrastive Learning with Viewmaker Networks April 20, 2021 economy AI and the Future of Work December 20, 2018 education Towards an Educational Revolution Through Chatbots July 12, 2019 elmo BERT, ELMo, & GPT-2: How Contextual are Contextualized Word Representations? March 24, 2020 entity linking Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation November 12, 2020 epidemiological modeling Supporting COVID-19 policy response with large-scale mobility-based modeling August 16, 2021 ethics Measuring Bias in NLP (with Confidence!) November 11, 2020 In Favor of Developing Ethical Best Practices in AI Research February 21, 2019 explanation Faithful, Interpretable Model Explanations via Causal Abstraction October 31, 2022 Learning from Language Explanations November 23, 2020 fairness From Discrimination in Machine Learning to Discrimination in Law, Part 2: Disparate Impact December 23, 2022 From Discrimination in Machine Learning to Discrimination in Law, Part 1: Disparate Treatment December 5, 2022 Selective Classification Can Magnify Disparities Across Groups October 13, 2021 Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately January 24, 2021 Measuring Bias in NLP (with Confidence!) November 11, 2020 Controllable Fairness in Machine Learning May 27, 2019 fairness in machine learning From Discrimination in Machine Learning to Discrimination in Law, Part 2: Disparate Impact December 23, 2022 From Discrimination in Machine Learning to Discrimination in Law, Part 1: Disparate Treatment December 5, 2022 feature selection Text Feature Selection for Causal Inference December 5, 2019 few-shot learning How does in-context learning work? A framework for understanding the differences from traditional supervised learning August 1, 2022 Grading Complex Interactive Coding Programs with Reinforcement Learning March 28, 2022 fill in the blanks How to Fill in the Blanks with Language Models September 10, 2020 generalization Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation November 12, 2020 gpt-2 BERT, ELMo, & GPT-2: How Contextual are Contextualized Word Representations? March 24, 2020 gpt-3 How does in-context learning work? A framework for understanding the differences from traditional supervised learning August 1, 2022 Measuring Bias in NLP (with Confidence!) November 11, 2020 gpt2 BERT, ELMo, & GPT-2: How Contextual are Contextualized Word Representations? March 24, 2020 gpt3 Measuring Bias in NLP (with Confidence!) November 11, 2020 graph LinkBERT: Improving Language Model Training with Document Link May 31, 2022 graph neural networks Reasoning with Language Models and Knowledge Graphs for Question Answering July 12, 2021 grounding Learning from Language Explanations November 23, 2020 hci Towards an Educational Revolution Through Chatbots July 12, 2019 Learning to Generate Human–Object Interactions May 7, 2019 human-robot interaction Conventions in Multi-Agent Collaboration April 28, 2021 Back to the Future: Planning-Aware Trajectory Forecasting for Autonomous Driving June 25, 2020 When Humans Aren’t Optimal: Robots that Collaborate with Risk-Aware Humans March 17, 2020 Influencing Leading and Following in Human-Robot Teams June 24, 2019 Learning Reward Functions by Integrating Human Demonstrations and Preferences June 22, 2019 hyperlink LinkBERT: Improving Language Model Training with Document Link May 31, 2022 il Leveraging Compositionality for One-Shot Imitation Learning May 6, 2020 RoboTurk: Human Reasoning and Dexterity for Large-Scale Dataset Creation November 8, 2019 ilm How to Fill in the Blanks with Language Models September 10, 2020 imitation learning Learning to Imitate November 1, 2022 What Matters in Learning from Offline Human Demonstrations for Robot Manipulation August 8, 2021 GTI: Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations October 7, 2020 in-context learning How does in-context learning work? A framework for understanding the differences from traditional supervised learning August 1, 2022 infilling How to Fill in the Blanks with Language Models September 10, 2020 infilling by language modeling How to Fill in the Blanks with Language Models September 10, 2020 information retrieval Building Scalable, Explainable, and Adaptive NLP Models with Retrieval October 5, 2021 interpretability Faithful, Interpretable Model Explanations via Causal Abstraction October 31, 2022 Do Language Models Know How Heavy an Elephant Is? February 17, 2021 Text Feature Selection for Causal Inference December 5, 2019 Progress Toward Safe and Reliable AI May 2, 2019 inverse reinforcement-learning Learning to Imitate November 1, 2022 iq-learn Learning to Imitate November 1, 2022 ir Building Scalable, Explainable, and Adaptive NLP Models with Retrieval October 5, 2021 k-means BanditPAM: Almost Linear-Time k-medoids Clustering via Multi-Armed Bandits December 17, 2021 k-medoids BanditPAM: Almost Linear-Time k-medoids Clustering via Multi-Armed Bandits December 17, 2021 knowledge LinkBERT: Improving Language Model Training with Document Link May 31, 2022 Reasoning with Language Models and Knowledge Graphs for Question Answering July 12, 2021 knowledge graph Reasoning with Language Models and Knowledge Graphs for Question Answering July 12, 2021 language model LinkBERT: Improving Language Model Training with Document Link May 31, 2022 Reasoning with Language Models and Knowledge Graphs for Question Answering July 12, 2021 How to Fill in the Blanks with Language Models September 10, 2020 language modeling LinkBERT: Improving Language Model Training with Document Link May 31, 2022 language models How does in-context learning work? A framework for understanding the differences from traditional supervised learning August 1, 2022 large language models How does in-context learning work? A framework for understanding the differences from traditional supervised learning August 1, 2022 law From Discrimination in Machine Learning to Discrimination in Law, Part 2: Disparate Impact December 23, 2022 From Discrimination in Machine Learning to Discrimination in Law, Part 1: Disparate Treatment December 5, 2022 learning Controlling Assistive Robots with Learned Latent Actions November 11, 2019 Learning from My Partner’s Actions: Roles in Decentralized Robot Teams October 28, 2019 Learning to Generate Human–Object Interactions May 7, 2019 learning from humans Influencing Leading and Following in Human-Robot Teams June 24, 2019 Learning Reward Functions by Integrating Human Demonstrations and Preferences June 22, 2019 lm How to Fill in the Blanks with Language Models September 10, 2020 long sequences Can Longer Sequences Help Take the Next Leap in AI? June 9, 2022 machine learning From Discrimination in Machine Learning to Discrimination in Law, Part 2: Disparate Impact December 23, 2022 From Discrimination in Machine Learning to Discrimination in Law, Part 1: Disparate Treatment December 5, 2022 Learning to Imitate November 1, 2022 Faithful, Interpretable Model Explanations via Causal Abstraction October 31, 2022 How does in-context learning work? A framework for understanding the differences from traditional supervised learning August 1, 2022 Can Longer Sequences Help Take the Next Leap in AI? June 9, 2022 LinkBERT: Improving Language Model Training with Document Link May 31, 2022 Understanding Deep Learning Algorithms that Leverage Unlabeled Data, Part 2: Contrastive Learning April 13, 2022 Discovering the systematic errors made by machine learning models April 7, 2022 Understanding Deep Learning Algorithms that Leverage Unlabeled Data, Part 1: Self-training February 24, 2022 How to Improve User Experience (and Behavior): Three Papers from Stanford's Alexa Prize Team February 1, 2022 BanditPAM: Almost Linear-Time k-medoids Clustering via Multi-Armed Bandits December 17, 2021 Selective Classification Can Magnify Disparities Across Groups October 13, 2021 Break-It-Fix-It: Unsupervised Learning for Fixing Source Code Errors September 21, 2021 Our Journey towards Data-Centric AI: A Retrospective September 15, 2021 Reasoning with Language Models and Knowledge Graphs for Question Answering July 12, 2021 Extrapolating to Unnatural Language Processing with GPT-3's In-context Learning: The Good, the Bad, and the Mysterious May 28, 2021 Neural Mechanics: Symmetry and Broken Conservation Laws In Deep Learning Dynamics February 25, 2021 Do Language Models Know How Heavy an Elephant Is? February 17, 2021 Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately January 24, 2021 A Model-Based Approach Towards Identifying the Brain's Learning Algorithms December 9, 2020 Learning from Language Explanations November 23, 2020 Learning to Fix Programs from Error Messages November 8, 2020 A Topology Layer for Machine Learning August 23, 2019 meta-learning Adapting on the Fly to Test Time Distribution Shift November 5, 2020 Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning August 26, 2020 ml From Discrimination in Machine Learning to Discrimination in Law, Part 2: Disparate Impact December 23, 2022 From Discrimination in Machine Learning to Discrimination in Law, Part 1: Disparate Treatment December 5, 2022 Learning to Imitate November 1, 2022 Can Longer Sequences Help Take the Next Leap in AI? June 9, 2022 LinkBERT: Improving Language Model Training with Document Link May 31, 2022 Understanding Deep Learning Algorithms that Leverage Unlabeled Data, Part 2: Contrastive Learning April 13, 2022 Discovering the systematic errors made by machine learning models April 7, 2022 Understanding Deep Learning Algorithms that Leverage Unlabeled Data, Part 1: Self-training February 24, 2022 How to Improve User Experience (and Behavior): Three Papers from Stanford's Alexa Prize Team February 1, 2022 BanditPAM: Almost Linear-Time k-medoids Clustering via Multi-Armed Bandits December 17, 2021 Selective Classification Can Magnify Disparities Across Groups October 13, 2021 Break-It-Fix-It: Unsupervised Learning for Fixing Source Code Errors September 21, 2021 Our Journey towards Data-Centric AI: A Retrospective September 15, 2021 What Matters in Learning from Offline Human Demonstrations for Robot Manipulation August 8, 2021 Reasoning with Language Models and Knowledge Graphs for Question Answering July 12, 2021 Extrapolating to Unnatural Language Processing with GPT-3's In-context Learning: The Good, the Bad, and the Mysterious May 28, 2021 Neural Mechanics: Symmetry and Broken Conservation Laws In Deep Learning Dynamics February 25, 2021 Do Language Models Know How Heavy an Elephant Is? February 17, 2021 Learning from Language Explanations November 23, 2020 Learning to Fix Programs from Error Messages November 8, 2020 Adapting on the Fly to Test Time Distribution Shift November 5, 2020 GTI: Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations October 7, 2020 Safety Validation of Black-Box Autonomous Systems August 31, 2020 Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning August 26, 2020 Back to the Future: Planning-Aware Trajectory Forecasting for Autonomous Driving June 25, 2020 Making Sense of Vision and Touch: Multimodal Representations for Contact-Rich Tasks May 18, 2020 Leveraging Compositionality for One-Shot Imitation Learning May 6, 2020 Automating Data Augmentation: Practice, Theory and New Direction April 24, 2020 Text Feature Selection for Causal Inference December 5, 2019 Powerful Abstractions for Programmatically Building and Managing Training Sets June 21, 2019 Controllable Fairness in Machine Learning May 27, 2019 Progress Toward Safe and Reliable AI May 2, 2019 Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization April 17, 2019 Weak Supervision: A New Programming Paradigm for Machine Learning March 10, 2019 mobility networks Supporting COVID-19 policy response with large-scale mobility-based modeling August 16, 2021 model-based learning RoboNet: A Dataset for Large-Scale Multi-Robot Learning November 26, 2019 multi-agent systems Conventions in Multi-Agent Collaboration April 28, 2021 Learning from My Partner’s Actions: Roles in Decentralized Robot Teams October 28, 2019 multi-armed bandits BanditPAM: Almost Linear-Time k-medoids Clustering via Multi-Armed Bandits December 17, 2021 multi-hop reasoning Building Scalable, Explainable, and Adaptive NLP Models with Retrieval October 5, 2021 multiarmed bandits BanditPAM: Almost Linear-Time k-medoids Clustering via Multi-Armed Bandits December 17, 2021 multimodal Adaptive Energy-Efficient Routing for Autonomous Vehicles July 18, 2019 named entity disambiguation Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation November 12, 2020 natural language processing Reward Isn't Free: Supervising Robot Learning with Language and Video from the Web January 21, 2022 Building Scalable, Explainable, and Adaptive NLP Models with Retrieval October 5, 2021 neural generation Inside Chirpy Cardinal: Stanford's Open-Source Social Chatbot that Won 2nd place in the Alexa Prize April 9, 2021 nlp How does in-context learning work? A framework for understanding the differences from traditional supervised learning August 1, 2022 LinkBERT: Improving Language Model Training with Document Link May 31, 2022 How to Improve User Experience (and Behavior): Three Papers from Stanford's Alexa Prize Team February 1, 2022 Selective Classification Can Magnify Disparities Across Groups October 13, 2021 Building Scalable, Explainable, and Adaptive NLP Models with Retrieval October 5, 2021 Break-It-Fix-It: Unsupervised Learning for Fixing Source Code Errors September 21, 2021 Reasoning with Language Models and Knowledge Graphs for Question Answering July 12, 2021 Extrapolating to Unnatural Language Processing with GPT-3's In-context Learning: The Good, the Bad, and the Mysterious May 28, 2021 Inside Chirpy Cardinal: Stanford's Open-Source Social Chatbot that Won 2nd place in the Alexa Prize April 9, 2021 Do Language Models Know How Heavy an Elephant Is? February 17, 2021 Learning from Language Explanations November 23, 2020 Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation November 12, 2020 Measuring Bias in NLP (with Confidence!) November 11, 2020 Learning to Fix Programs from Error Messages November 8, 2020 How to Fill in the Blanks with Language Models September 10, 2020 Finding Cross-Lingual Syntax in Multilingual BERT May 26, 2020 BERT, ELMo, & GPT-2: How Contextual are Contextualized Word Representations? March 24, 2020 Text Feature Selection for Causal Inference December 5, 2019 Answering Complex Open-domain Questions at Scale October 21, 2019 What makes a good conversation? August 18, 2019 Beyond Local Pattern Matching: Recent Advances in Machine Reading February 26, 2019 open source Inside Chirpy Cardinal: Stanford's Open-Source Social Chatbot that Won 2nd place in the Alexa Prize April 9, 2021 open-domain question answering Building Scalable, Explainable, and Adaptive NLP Models with Retrieval October 5, 2021 opinion In Favor of Developing Ethical Best Practices in AI Research February 21, 2019 optimization Altruistic Autonomy: Beating Congestion on Shared Roads November 26, 2018 parity Controllable Fairness in Machine Learning May 27, 2019 physics Neural Mechanics: Symmetry and Broken Conservation Laws In Deep Learning Dynamics February 25, 2021 planning Sequential Problem Solving by Hierarchical Planning in Latent Spaces April 10, 2020 Adaptive Energy-Efficient Routing for Autonomous Vehicles July 18, 2019 prediction Back to the Future: Planning-Aware Trajectory Forecasting for Autonomous Driving June 25, 2020 When Humans Aren’t Optimal: Robots that Collaborate with Risk-Aware Humans March 17, 2020 preferences Influencing Leading and Following in Human-Robot Teams June 24, 2019 Learning Reward Functions by Integrating Human Demonstrations and Preferences June 22, 2019 pretraining How does in-context learning work? A framework for understanding the differences from traditional supervised learning August 1, 2022 LinkBERT: Improving Language Model Training with Document Link May 31, 2022 Broadening the Reach of Contrastive Learning with Viewmaker Networks April 20, 2021 probing Do Language Models Know How Heavy an Elephant Is? February 17, 2021 program repair Break-It-Fix-It: Unsupervised Learning for Fixing Source Code Errors September 21, 2021 program synthesis Break-It-Fix-It: Unsupervised Learning for Fixing Source Code Errors September 21, 2021 Learning to Fix Programs from Error Messages November 8, 2020 prototype network Meta-Learning Student Feedback to 16,000 Solutions July 20, 2021 publication Stanford AI Lab Papers and Talks at ICLR 2023 May 1, 2023 Stanford AI Lab Papers and Talks at CoRL 2022 December 16, 2022 Stanford AI Lab Papers and Talks at EMNLP 2022 December 3, 2022 Stanford AI Lab Papers and Talks at NeurIPS 2022 November 30, 2022 Learning to Imitate November 1, 2022 Stanford AI Lab Papers and Talks at IROS 2022 October 25, 2022 Stanford AI Lab Papers and Talks at ECCV 2022 October 25, 2022 Stanford AI Lab Papers and Talks at ICML 2022 July 18, 2022 Stanford AI Lab Papers and Talks at NAACL 2022 July 10, 2022 Stanford AI Lab Papers and Talks at CVPR 2022 June 21, 2022 Stanford AI Lab Robotics Papers (ICRA and RSS 2022) June 20, 2022 LinkBERT: Improving Language Model Training with Document Link May 31, 2022 Stanford AI Lab Papers and Talks at ACL 2022 May 25, 2022 Stanford AI Lab Papers and Talks at ICLR 2022 April 25, 2022 Stanford AI Lab Papers and Talks at AAAI 2022 February 22, 2022 BanditPAM: Almost Linear-Time k-medoids Clustering via Multi-Armed Bandits December 17, 2021 Stanford AI Lab Papers and Talks at NeurIPS 2021 December 6, 2021 Stanford AI Lab Papers at EMNLP/CoNLL 2021 November 5, 2021 Stanford AI Lab Papers at CoRL 2021 November 5, 2021 Stanford AI Lab Papers at ICCV 2021 October 8, 2021 Break-It-Fix-It: Unsupervised Learning for Fixing Source Code Errors September 21, 2021 Stanford AI Lab Papers at ACL-IJCNLP 2021 August 2, 2021 Stanford AI Lab Papers and Talks at ICML 2021 July 17, 2021 Reasoning with Language Models and Knowledge Graphs for Question Answering July 12, 2021 AGQA: A Benchmark for Compositional, Spatio-Temporal Reasoning June 21, 2021 Stanford AI Lab Papers and Talks at CVPR 2021 June 20, 2021 Stanford AI Lab Papers and Talks at ICLR 2021 May 3, 2021 Stanford AI Lab Papers and Talks at AISTATS 2021 April 13, 2021 Stanford AI Lab Papers and Talks at NeurIPS 2020 December 6, 2020 Stanford AI Lab Papers and Talks at CoRL 2020 November 16, 2020 Stanford AI Lab Papers and Talks at EMNLP 2020 November 15, 2020 Stanford AI Lab Papers and Talks at ECCV 2020 August 23, 2020 Stanford AI Lab Papers and Talks at ICML 2020 July 11, 2020 Stanford Papers and Workshops at RSS 2020 July 9, 2020 Stanford AI Lab Papers and Talks at ACL 2020 July 6, 2020 Stanford AI Lab Papers and Talks at CVPR 2020 June 15, 2020 SAIL and Stanford Robotics at ICRA 2020 May 30, 2020 q-learning Learning to Imitate November 1, 2022