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Author Information
Guy Van den Broeck (University of California, Los Angeles)
Ishita Dasgupta (DeepMind)
Subbarao Kambhampati (Arizona State University)

Subbarao Kambhampati is a professor of computer science at Arizona State University. Kambhampati studies fundamental problems in planning and decision making, motivated in particular by the challenges of human-aware AI systems. He is a fellow of Association for the Advancement of Artificial Intelligence, American Association for the Advancement of Science, and Association for Computing machinery, and was an NSF Young Investigator. He served as the president of the Association for the Advancement of Artificial Intelligence, a trustee of the International Joint Conference on Artificial Intelligence, the chair of AAAS Section T (Information, Communication and Computation), and a founding board member of Partnership on AI. Kambhampati’s research as well as his views on the progress and societal impacts of AI have been featured in multiple national and international media outlets. He can be followed on Twitter @rao2z.
Jiajun Wu (Stanford University)
Jiajun Wu is a Visiting Faculty Researcher at Google Research, New York City. In July 2020, he will join Stanford University as an Assistant Professor of Computer Science. He studies machine perception, reasoning, and its interaction with the physical world, drawing inspiration from human cognition.
Xi Victoria Lin (Meta AI)
Samy Bengio (Apple MLR)
Beliz Gunel (Google Research)
More from the Same Authors
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2023 : On the Planning Abilities of Large Language Models - A Critical Investigation »
Karthik Valmeekam · Matthew Marquez · Sarath Sreedharan · Subbarao Kambhampati -
2023 : Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning »
Lin Guan · Karthik Valmeekam · Sarath Sreedharan · Subbarao Kambhampati -
2023 : Learning and Leveraging Verifiers to Improve Planning Capabilities of Pre-trained Language Models »
Daman Arora · Subbarao Kambhampati -
2023 : A Pseudo-Semantic Loss for Deep Generative Models with Logical Constraints »
Kareem Ahmed · Kai-Wei Chang · Guy Van den Broeck -
2023 : Collapsed Inference for Bayesian Deep Learning »
Zhe Zeng · Guy Van den Broeck -
2023 : SIMPLE: A Gradient Estimator for $k$-subset Sampling »
Kareem Ahmed · Zhe Zeng · Mathias Niepert · Guy Van den Broeck -
2023 : Probabilistic Task-Adaptive Graph Rewiring »
Chendi Qian · Andrei Manolache · Kareem Ahmed · Zhe Zeng · Guy Van den Broeck · Mathias Niepert · Christopher Morris -
2023 : A Unified Approach to Count-Based Weakly-Supervised Learning »
Vinay Shukla · Zhe Zeng · Kareem Ahmed · Guy Van den Broeck -
2023 : Exploiting Action Distances for Reward Learning from Human Preferences »
Mudit Verma · Siddhant Bhambri · Subbarao Kambhampati -
2023 : Relative Behavioral Attributes: Filling the Gap between Symbolic Goal Specification and Reward Learning from Human Preferences »
Lin Guan · Karthik Valmeekam · Subbarao Kambhampati -
2023 : Preference Proxies: Evaluating Large Language Models in capturing Human Preferences in Human-AI Tasks »
Mudit Verma · Siddhant Bhambri · Subbarao Kambhampati -
2023 : Knowledge and Skill Acquisition through Language Model Pre-training and Instruction-tuning »
Xi Victoria Lin -
2023 : Concept Learning Across Domains and Modalities »
Jiajun Wu -
2023 : Avenging Polanyi's Revenge: Exploiting the Approximate Omniscience of LLMs in Planning without Deluding Yourself In the Process »
Subbarao Kambhampati -
2023 : Preference Proxies: Evaluating Large Language Models in capturing Human Preferences in Human-AI Tasks »
Mudit Verma · Siddhant Bhambri · Subbarao Kambhampati -
2023 : Reasoning Biases in Language Models »
Ishita Dasgupta -
2023 : AI can Learn from Data. But can it Learn to Reason? »
Guy Van den Broeck -
2023 : Generalization on the Unseen, Logic Reasoning and Degree Curriculum »
Samy Bengio -
2023 Workshop: Knowledge and Logical Reasoning in the Era of Data-driven Learning »
Nezihe Merve Gürel · Bo Li · Theodoros Rekatsinas · Beliz Gunel · Alberto Sngiovanni Vincentelli · Paroma Varma -
2023 Panel: The Societal Impacts of AI »
Sanmi Koyejo · Samy Bengio · Ashia Wilson · Kirikowhai Mikaere · Joelle Pineau -
2023 Poster: LEVER: Learning to Verify Language-to-Code Generation with Execution »
Ansong Ni · Srinivasan Iyer · Dragomir Radev · Veselin Stoyanov · Scott Yih · Sida Wang · Xi Victoria Lin -
2023 Poster: Modeling Dynamic Environments with Scene Graph Memory »
Andrey Kurenkov · Michael Lingelbach · Tanmay Agarwal · Emily Jin · Chengshu Li · Ruohan Zhang · Li Fei-Fei · Jiajun Wu · Silvio Savarese · Roberto Martín-Martín -
2023 Oral: Tractable Control for Autoregressive Language Generation »
Honghua Zhang · Meihua Dang · Nanyun Peng · Guy Van den Broeck -
2023 Poster: Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits »
Xuejie Liu · Anji Liu · Guy Van den Broeck · Yitao Liang -
2023 Poster: Motion Question Answering via Modular Motion Programs »
Mark Endo · Joy Hsu · Jiaman Li · Jiajun Wu -
2023 Poster: Generalization on the Unseen, Logic Reasoning and Degree Curriculum »
Emmanuel Abbe · Samy Bengio · Aryo Lotfi · Kevin Rizk -
2023 Poster: Distilling Internet-Scale Vision-Language Models into Embodied Agents »
Theodore R Sumers · Kenneth Marino · Arun Ahuja · Rob Fergus · Ishita Dasgupta -
2023 Oral: Generalization on the Unseen, Logic Reasoning and Degree Curriculum »
Emmanuel Abbe · Samy Bengio · Aryo Lotfi · Kevin Rizk -
2023 Poster: Tractable Control for Autoregressive Language Generation »
Honghua Zhang · Meihua Dang · Nanyun Peng · Guy Van den Broeck -
2022 : Session 3: New Computational Technologies for Reasoning »
Armando Solar-Lezama · Guy Van den Broeck · Jan-Willem van de Meent · Charles Sutton -
2022 : Session 2: Reasoning in Brains vs Machines »
Emily Mackevicius · Kim Stachenfeld · tyler bonnen · Ishita Dasgupta -
2022 Poster: Tell me why! Explanations support learning relational and causal structure »
Andrew Lampinen · Nicholas Roy · Ishita Dasgupta · Stephanie Chan · Allison Tam · James McClelland · Chen Yan · Adam Santoro · Neil Rabinowitz · Jane Wang · Feilx Hill -
2022 Spotlight: Tell me why! Explanations support learning relational and causal structure »
Andrew Lampinen · Nicholas Roy · Ishita Dasgupta · Stephanie Chan · Allison Tam · James McClelland · Chen Yan · Adam Santoro · Neil Rabinowitz · Jane Wang · Feilx Hill -
2022 Poster: Leveraging Approximate Symbolic Models for Reinforcement Learning via Skill Diversity »
Lin Guan · Sarath Sreedharan · Subbarao Kambhampati -
2022 Spotlight: Leveraging Approximate Symbolic Models for Reinforcement Learning via Skill Diversity »
Lin Guan · Sarath Sreedharan · Subbarao Kambhampati -
2022 Poster: Distinguishing rule- and exemplar-based generalization in learning systems »
Ishita Dasgupta · Erin Grant · Thomas Griffiths -
2022 Spotlight: Distinguishing rule- and exemplar-based generalization in learning systems »
Ishita Dasgupta · Erin Grant · Thomas Griffiths -
2021 Poster: Probabilistic Generating Circuits »
Honghua Zhang · Brendan Juba · Guy Van den Broeck -
2021 Oral: Probabilistic Generating Circuits »
Honghua Zhang · Brendan Juba · Guy Van den Broeck -
2020 : On the Relationship Between Probabilistic Circuits and Determinantal Point Processes »
Honghua Zhang · Steven Holtzen · Guy Van den Broeck -
2020 Workshop: 2nd ICML Workshop on Human in the Loop Learning (HILL) »
Shanghang Zhang · Xin Wang · Fisher Yu · Jiajun Wu · Trevor Darrell -
2020 Poster: Visual Grounding of Learned Physical Models »
Yunzhu Li · Toru Lin · Kexin Yi · Daniel Bear · Daniel Yamins · Jiajun Wu · Josh Tenenbaum · Antonio Torralba -
2020 Poster: Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits »
Robert Peharz · Steven Lang · Antonio Vergari · Karl Stelzner · Alejandro Molina · Martin Trapp · Guy Van den Broeck · Kristian Kersting · Zoubin Ghahramani -
2020 Poster: Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing »
Zhe Zeng · Paolo Morettin · Fanqi Yan · Antonio Vergari · Guy Van den Broeck -
2020 Affinity Workshop: New In ML »
Zhen Xu · Sparkle Russell-Puleri · Zhengying Liu · Sinead A Williamson · Matthias W Seeger · Wei-Wei Tu · Samy Bengio · Isabelle Guyon -
2019 Workshop: Identifying and Understanding Deep Learning Phenomena »
Hanie Sedghi · Samy Bengio · Kenji Hata · Aleksander Madry · Ari Morcos · Behnam Neyshabur · Maithra Raghu · Ali Rahimi · Ludwig Schmidt · Ying Xiao -
2019 Poster: Area Attention »
Yang Li · Lukasz Kaiser · Samy Bengio · Si Si -
2019 Poster: Neurally-Guided Structure Inference »
Sidi Lu · Jiayuan Mao · Josh Tenenbaum · Jiajun Wu -
2019 Oral: Area Attention »
Yang Li · Lukasz Kaiser · Samy Bengio · Si Si -
2019 Oral: Neurally-Guided Structure Inference »
Sidi Lu · Jiayuan Mao · Josh Tenenbaum · Jiajun Wu -
2018 Poster: Sound Abstraction and Decomposition of Probabilistic Programs »
Steven Holtzen · Guy Van den Broeck · Todd Millstein -
2018 Oral: Sound Abstraction and Decomposition of Probabilistic Programs »
Steven Holtzen · Guy Van den Broeck · Todd Millstein -
2018 Poster: Fast Decoding in Sequence Models Using Discrete Latent Variables »
Lukasz Kaiser · Samy Bengio · Aurko Roy · Ashish Vaswani · Niki Parmar · Jakob Uszkoreit · Noam Shazeer -
2018 Oral: Fast Decoding in Sequence Models Using Discrete Latent Variables »
Lukasz Kaiser · Samy Bengio · Aurko Roy · Ashish Vaswani · Niki Parmar · Jakob Uszkoreit · Noam Shazeer -
2018 Poster: A Semantic Loss Function for Deep Learning with Symbolic Knowledge »
Jingyi Xu · Zilu Zhang · Tal Friedman · Yitao Liang · Guy Van den Broeck -
2018 Oral: A Semantic Loss Function for Deep Learning with Symbolic Knowledge »
Jingyi Xu · Zilu Zhang · Tal Friedman · Yitao Liang · Guy Van den Broeck -
2017 Workshop: Reproducibility in Machine Learning Research »
Rosemary Nan Ke · Anirudh Goyal · Alex Lamb · Joelle Pineau · Samy Bengio · Yoshua Bengio -
2017 Poster: Device Placement Optimization with Reinforcement Learning »
Azalia Mirhoseini · Hieu Pham · Quoc Le · benoit steiner · Mohammad Norouzi · Rasmus Larsen · Yuefeng Zhou · Naveen Kumar · Samy Bengio · Jeff Dean -
2017 Talk: Device Placement Optimization with Reinforcement Learning »
Azalia Mirhoseini · Hieu Pham · Quoc Le · benoit steiner · Mohammad Norouzi · Rasmus Larsen · Yuefeng Zhou · Naveen Kumar · Samy Bengio · Jeff Dean -
2017 Poster: Sharp Minima Can Generalize For Deep Nets »
Laurent Dinh · Razvan Pascanu · Samy Bengio · Yoshua Bengio -
2017 Talk: Sharp Minima Can Generalize For Deep Nets »
Laurent Dinh · Razvan Pascanu · Samy Bengio · Yoshua Bengio