Thomson Reuters' Solution for Triple Ranking in the FEIII 2017 Challenge. - Elizabeth Roman; Brian Ulicny; Yilun Du; Srijith Poduval; Allan Ko (DSMM@SIGMOD, 2017)

Thomson Reuters' Submission to the FEIII 2017 Challenge Non-scored Tasks. - Elizabeth Roman; Brian Ulicny; Yilun Du; Srijith Poduval; Allan Ko (DSMM@SIGMOD, 2017)

Learning to Exploit Stability for 3D Scene Parsing. - Yilun Du; Zhijian Liu; Hector Basevi; Ales Leonardis; Bill Freeman; Josh Tenenbaum 001; Jiajun Wu 001 (NeurIPS, 2018)

Model-Based Planning with Energy-Based Models. - Yilun Du; Toru Lin; Igor Mordatch (CoRL, 2019)

Task-Agnostic Dynamics Priors for Deep Reinforcement Learning. - Yilun Du; Karthik Narasimhan (ICML, 2019)

Implicit Generation and Modeling with Energy Based Models. - Yilun Du; Igor Mordatch (NeurIPS, 2019)

Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents. - Joseph Suarez; Yilun Du; Phillip Isola; Igor Mordatch (CoRR, 2019)

Implicit Generation and Generalization in Energy-Based Models. - Yilun Du; Igor Mordatch (CoRR, 2019)

An Empirical Study on Hyperparameters and their Interdependence for RL Generalization. - Xingyou Song; Yilun Du; Jacob Jackson (CoRR, 2019)

Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. - Joseph Suarez; Yilun Du; Igor Mordatch; Phillip Isola (AAMAS, 2020)

A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects. - Anthony Simeonov; Yilun Du; Beomjoon Kim; Francois Robert Hogan; Joshua B. Tenenbaum; Pulkit Agrawal 001; Alberto Rodriguez 003 (CoRL, 2020)

Energy-based models for atomic-resolution protein conformations. - Yilun Du; Joshua Meier; Jerry Ma; Rob Fergus; Alexander Rives (ICLR, 2020)

Observational Overfitting in Reinforcement Learning. - Xingyou Song; Yiding Jiang; Stephen Tu; Yilun Du; Behnam Neyshabur (ICLR, 2020)

Compositional Visual Generation with Energy Based Models. - Yilun Du; Shuang Li 013; Igor Mordatch (NeurIPS, 2020)

Compositional Visual Generation and Inference with Energy Based Models. - Yilun Du; Shuang Li 013; Igor Mordatch (CoRR, 2020)

Learning Online Data Association. - Yilun Du; Joshua B. Tenenbaum; Tomás Lozano-Pérez; Leslie Pack Kaelbling (CoRR, 2020)

Energy-Based Models for Continual Learning. - Shuang Li 013; Yilun Du; Gido M. van de Ven; Antonio Torralba 001; Igor Mordatch (CoRR, 2020)

Curious Representation Learning for Embodied Intelligence. - Yilun Du; Chuang Gan 001; Phillip Isola (ICCV, 2021)

Neural Radiance Flow for 4D View Synthesis and Video Processing. - Yilun Du; Yinan Zhang; Hong-Xing Yu; Joshua B. Tenenbaum; Jiajun Wu 001 (ICCV, 2021)

Weakly Supervised Human-Object Interaction Detection in Video via Contrastive Spatiotemporal Regions. - Shuang Li 013; Yilun Du; Antonio Torralba 001; Josef Sivic; Bryan C. Russell (ICCV, 2021)

3D Shape Generation and Completion through Point-Voxel Diffusion. - Linqi Zhou; Yilun Du; Jiajun Wu 001 (ICCV, 2021)

Unsupervised Discovery of 3D Physical Objects from Video. - Yilun Du; Kevin A. Smith 001; Tomer D. Ullman; Joshua B. Tenenbaum; Jiajun Wu 001 (ICLR, 2021)

Improved Contrastive Divergence Training of Energy-Based Models. - Yilun Du; Shuang Li 013; Joshua B. Tenenbaum; Igor Mordatch (ICML, 2021)

Learning Signal-Agnostic Manifolds of Neural Fields. - Yilun Du; Katie Collins; Josh Tenenbaum 001; Vincent Sitzmann (NeurIPS, 2021)

Unsupervised Learning of Compositional Energy Concepts. - Yilun Du; Shuang Li 013; Yash Sharma 001; Josh Tenenbaum 001; Igor Mordatch (NeurIPS, 2021)

Learning to Compose Visual Relations. - Nan Liu 010; Shuang Li 013; Yilun Du; Josh Tenenbaum 001; Antonio Torralba 001 (NeurIPS, 2021)

The Neural MMO Platform for Massively Multiagent Research. - Joseph Suarez; Yilun Du; Clare Zhu; Igor Mordatch; Phillip Isola (NeurIPS Datasets and Benchmarks, 2021)

Quark Self-Energy and Condensates in NJL Model with External Magnetic Field. - Juan Liu; Yilun Du; Song Shi (Symmetry, 2021)

Energy-Based Models for Continual Learning. - Shuang Li 013; Yilun Du; Gido van de Ven; Igor Mordatch (CoLLAs, 2022)

Streaming Inference for Infinite Non-Stationary Clustering. - Rylan Schaeffer; Gabrielle Kaili-May Liu; Yilun Du; Scott Linderman; Ila Rani Fiete (CoLLAs, 2022)

MIRA: Mental Imagery for Robotic Affordances. - Yen-Chen Lin; Pete Florence; Andy Zeng 001; Jonathan T. Barron; Yilun Du; Wei-Chiu Ma; Anthony Simeonov; Alberto Rodriguez Garcia; Phillip Isola (CoRL, 2022)

SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields. - Anthony Simeonov; Yilun Du; Yen-Chen Lin; Alberto Rodriguez Garcia; Leslie Pack Kaelbling; Tomás Lozano-Pérez; Pulkit Agrawal 001 (CoRL, 2022)

Kubric: A scalable dataset generator. - Klaus Greff; Francois Belletti; Lucas Beyer; Carl Doersch; Yilun Du; Daniel Duckworth; David J. Fleet; Dan Gnanapragasam; Florian Golemo; Charles Herrmann; Thomas Kipf; Abhijit Kundu; et al. (CVPR, 2022)

Compositional Visual Generation with Composable Diffusion Models. - Nan Liu 010; Shuang Li 013; Yilun Du; Antonio Torralba 001; Joshua B. Tenenbaum (ECCV (17), 2022)

Joint Channel Estimation and MAP Detection of Probabilistically Shaped QAM. - Yilun Du; Karim Abed-Meraim; Ouahbi Rekik (EUSIPCO, 2022)

Learning Iterative Reasoning through Energy Minimization. - Yilun Du; Shuang Li 013; Joshua B. Tenenbaum; Igor Mordatch (ICML, 2022)

Planning with Diffusion for Flexible Behavior Synthesis. - Michael Janner; Yilun Du; Joshua B. Tenenbaum; Sergey Levine (ICML, 2022)

Streaming Inference for Infinite Feature Models. - Rylan Schaeffer; Yilun Du; Gabrielle K. Liu; Ila Fiete (ICML, 2022)

Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation. - Anthony Simeonov; Yilun Du; Andrea Tagliasacchi; Joshua B. Tenenbaum; Alberto Rodriguez 003; Pulkit Agrawal 001; Vincent Sitzmann (ICRA, 2022)

Learning Object-Based State Estimators for Household Robots. - Yilun Du; Tomás Lozano-Pérez; Leslie Pack Kaelbling (IROS, 2022)

Robust Change Detection Based on Neural Descriptor Fields. - Jiahui Fu 002; Yilun Du; Kurran Singh; Joshua B. Tenenbaum; John J. Leonard (IROS, 2022)

3D Concept Grounding on Neural Fields. - Yining Hong; Yilun Du; Chunru Lin; Josh Tenenbaum 001; Chuang Gan 001 (NeurIPS, 2022)

Pre-Trained Language Models for Interactive Decision-Making. - Shuang Li 013; Xavier Puig; Chris Paxton 001; Yilun Du; Clinton Wang; Linxi Fan; Tao Chen 046; De-An Huang; Ekin Akyürek; Anima Anandkumar; Jacob Andreas; Igor Mordatch; et al. (NeurIPS, 2022)

Learning Neural Acoustic Fields. - Andrew F. Luo; Yilun Du; Michael J. Tarr; Josh Tenenbaum 001; Antonio Torralba 001; Chuang Gan 001 (NeurIPS, 2022)

Seeing 3D Objects in a Single Image via Self-Supervised Static-Dynamic Disentanglement. - Prafull Sharma; Ayush Tewari; Yilun Du; Sergey Zakharov; Rares Ambrus; Adrien Gaidon; William T. Freeman; Frédo Durand; Joshua B. Tenenbaum; Vincent Sitzmann (CoRR, 2022)

Self-conditioned Embedding Diffusion for Text Generation. - Robin Strudel; Corentin Tallec; Florent Altché; Yilun Du; Yaroslav Ganin; Arthur Mensch; Will Grathwohl; Nikolay Savinov; Sander Dieleman; Laurent Sifre; Rémi Leblond (CoRR, 2022)

SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields. - Anthony Simeonov; Yilun Du; Yen-Chen Lin; Alberto Rodriguez 003; Leslie Pack Kaelbling; Tomás Lozano-Pérez; Pulkit Agrawal 001 (CoRR, 2022)

Compositional Diffusion-Based Continuous Constraint Solvers. - Zhutian Yang; Jiayuan Mao; Yilun Du; Jiajun Wu 001; Joshua B. Tenenbaum; Tomás Lozano-Pérez; Leslie Pack Kaelbling (CoRL, 2023)

Learning to Render Novel Views from Wide-Baseline Stereo Pairs. - Yilun Du; Cameron Smith; Ayush Tewari; Vincent Sitzmann (CVPR, 2023)

3D Concept Learning and Reasoning from Multi-View Images. - Yining Hong; Chunru Lin; Yilun Du; Zhenfang Chen; Joshua B. Tenenbaum; Chuang Gan 001 (CVPR, 2023)

Unsupervised Compositional Concepts Discovery with Text-to-Image Generative Models. - Nan Liu 010; Yilun Du; Shuang Li 013; Joshua B. Tenenbaum; Antonio Torralba 001 (ICCV, 2023)

Is Conditional Generative Modeling all you need for Decision Making? - Anurag Ajay; Yilun Du; Abhi Gupta; Joshua B. Tenenbaum; Tommi S. Jaakkola; Pulkit Agrawal 001 (ICLR, 2023)

Planning with Sequence Models through Iterative Energy Minimization. - Hongyi Chen; Yilun Du; Yiye Chen; Joshua B. Tenenbaum; Patricio A. Vela (ICLR, 2023)

Composing Ensembles of Pre-trained Models via Iterative Consensus. - Shuang Li 013; Yilun Du; Joshua B. Tenenbaum; Antonio Torralba 001; Igor Mordatch (ICLR, 2023)

Neural Groundplans: Persistent Neural Scene Representations from a Single Image. - Prafull Sharma; Ayush Tewari; Yilun Du; Sergey Zakharov; Rares Andrei Ambrus; Adrien Gaidon; William T. Freeman; Frédo Durand; Joshua B. Tenenbaum; Vincent Sitzmann (ICLR, 2023)

Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. - Yilun Du; Conor Durkan; Robin Strudel; Joshua B. Tenenbaum; Sander Dieleman; Rob Fergus; Jascha Sohl-Dickstein; Arnaud Doucet; Will Sussman Grathwohl (ICML, 2023)

Inferring Relational Potentials in Interacting Systems. - Armand Comas Massague; Yilun Du; Christian Fernandez Lopez; Sandesh Ghimire; Mario Sznaier; Joshua B. Tenenbaum; Octavia I. Camps (ICML, 2023)

Local Neural Descriptor Fields: Locally Conditioned Object Representations for Manipulation. - Ethan Chun; Yilun Du; Anthony Simeonov; Tomás Lozano-Pérez; Leslie Pack Kaelbling (ICRA, 2023)

Visibility-Aware Navigation Among Movable Obstacles. - Jose Muguira-Iturralde; Aidan Curtis; Yilun Du; Leslie Pack Kaelbling; Tomás Lozano-Pérez (ICRA, 2023)

Compositional Foundation Models for Hierarchical Planning. - Anurag Ajay; Seungwook Han; Yilun Du; Shuang Li 013; Abhi Gupta; Tommi S. Jaakkola; Joshua B. Tenenbaum; Leslie Pack Kaelbling; Akash Srivastava; Pulkit Agrawal 001 (NeurIPS, 2023)

Secure Out-of-Distribution Task Generalization with Energy-Based Models. - Shengzhuang Chen; Long-Kai Huang; Jonathan Richard Schwarz; Yilun Du; Ying Wei 001 (NeurIPS, 2023)

Learning Universal Policies via Text-Guided Video Generation. - Yilun Du; Sherry Yang 001; Bo Dai 001; Hanjun Dai; Ofir Nachum; Josh Tenenbaum 001; Dale Schuurmans; Pieter Abbeel (NeurIPS, 2023)

3D-LLM: Injecting the 3D World into Large Language Models. - Yining Hong; Haoyu Zhen; Peihao Chen; Shuhong Zheng; Yilun Du; Zhenfang Chen; Chuang Gan 001 (NeurIPS, 2023)

FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow. - Cameron Smith; Yilun Du; Ayush Tewari; Vincent Sitzmann (NeurIPS, 2023)

DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models. - Tsun-Hsuan Johnson Wang; Juntian Zheng; Pingchuan Ma 002; Yilun Du; Byungchul Kim; Andrew Spielberg; Joshua B. Tenenbaum; Chuang Gan 001; Daniela Rus (NeurIPS, 2023)

Adaptive Online Replanning with Diffusion Models. - Siyuan Zhou; Yilun Du; Shun Zhang; Mengdi Xu; Yikang Shen; Wei Xiao 003; Dit-Yan Yeung; Chuang Gan 001 (NeurIPS, 2023)

Diffusion Policy: Visuomotor Policy Learning via Action Diffusion. - Cheng Chi; Siyuan Feng 003; Yilun Du; Zhenjia Xu; Eric Cousineau; Benjamin Burchfiel; Shuran Song (Robotics: Science and Systems, 2023)

NeuSE: Neural SE(3)-Equivariant Embedding for Consistent Spatial Understanding with Objects. - Jiahui Fu 002; Yilun Du; Kurran Singh; Joshua B. Tenenbaum; John J. Leonard (Robotics: Science and Systems, 2023)

StructDiffusion: Language-Guided Creation of Physically-Valid Structures using Unseen Objects. - Weiyu Liu; Yilun Du; Tucker Hermans; Sonia Chernova; Chris Paxton 001 (Robotics: Science and Systems, 2023)

Foundation Models for Decision Making: Problems, Methods, and Opportunities. - Sherry Yang 001; Ofir Nachum; Yilun Du; Jason Wei; Pieter Abbeel; Dale Schuurmans (CoRR, 2023)

Probabilistic Adaptation of Text-to-Video Models. - Mengjiao Yang 001; Yilun Du; Bo Dai 001; Dale Schuurmans; Joshua B. Tenenbaum; Pieter Abbeel (CoRR, 2023)

Learning Interactive Real-World Simulators. - Mengjiao Yang 001; Yilun Du; Kamyar Ghasemipour; Jonathan Tompson; Dale Schuurmans; Pieter Abbeel (CoRR, 2023)

Wake-Sleep Energy Based Models for Continual Learning. - Vaibhav Singh; Anna Choromanska; Shuang Li 013; Yilun Du (CVPR Workshops, 2024)

Large-Scale Reinforcement Learning for Diffusion Models. - Yinan Zhang; Eric Tzeng; Yilun Du; Dmitry Kislyuk (ECCV (63), 2024)

Training Diffusion Models with Reinforcement Learning. - Kevin Black; Michael Janner; Yilun Du; Ilya Kostrikov; Sergey Levine (ICLR, 2024)

Video Language Planning. - Yilun Du; Sherry Yang 001; Pete Florence; Fei Xia 002; Ayzaan Wahid; Brian Ichter; Pierre Sermanet; Tianhe Yu; Pieter Abbeel; Joshua B. Tenenbaum; Leslie Pack Kaelbling; Andy Zeng 001; et al. (ICLR, 2024)

Learning to Act from Actionless Videos through Dense Correspondences. - Po-Chen Ko; Jiayuan Mao; Yilun Du; Shao-Hua Sun; Joshua B. Tenenbaum (ICLR, 2024)

Learning to Jointly Understand Visual and Tactile Signals. - Yichen Li 004; Yilun Du; Chao Liu 021; Chao Liu 064; Francis Williams; Michael Foshey; Benjamin Eckart; Jan Kautz; Joshua B. Tenenbaum; Antonio Torralba 001; Wojciech Matusik (ICLR, 2024)

Compositional Generative Inverse Design. - Tailin Wu; Takashi Maruyama; Long Wei; Tao Zhang 102; Yilun Du; Gianluca Iaccarino; Jure Leskovec (ICLR, 2024)

Probabilistic Adaptation of Black-Box Text-to-Video Models. - Sherry Yang 001; Yilun Du; Bo Dai 001; Dale Schuurmans; Joshua B. Tenenbaum; Pieter Abbeel (ICLR, 2024)

Learning Interactive Real-World Simulators. - Sherry Yang 001; Yilun Du; Seyed Kamyar Seyed Ghasemipour; Jonathan Tompson; Leslie Pack Kaelbling; Dale Schuurmans; Pieter Abbeel (ICLR, 2024)

Building Cooperative Embodied Agents Modularly with Large Language Models. - Hongxin Zhang; Weihua Du; Jiaming Shan; Qinhong Zhou; Yilun Du; Joshua B. Tenenbaum; Tianmin Shu; Chuang Gan 001 (ICLR, 2024)

HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments. - Qinhong Zhou; Sunli Chen; Yisong Wang; Haozhe Xu; Weihua Du; Hongxin Zhang; Yilun Du; Joshua B. Tenenbaum; Chuang Gan 001 (ICLR, 2024)

Improving Factuality and Reasoning in Language Models through Multiagent Debate. - Yilun Du; Shuang Li 013; Antonio Torralba 001; Joshua B. Tenenbaum; Igor Mordatch (ICML, 2024)

Position: Compositional Generative Modeling: A Single Model is Not All You Need. - Yilun Du; Leslie Pack Kaelbling (ICML, 2024)

Learning Iterative Reasoning through Energy Diffusion. - Yilun Du; Jiayuan Mao; Joshua B. Tenenbaum (ICML, 2024)

Potential Based Diffusion Motion Planning. - Yunhao Luo 001; Chen Sun 002; Joshua B. Tenenbaum; Yilun Du (ICML, 2024)

Compositional Image Decomposition with Diffusion Models. - Jocelin Su; Nan Liu 010; Yanbo Wang; Joshua B. Tenenbaum; Yilun Du (ICML, 2024)

Position: Video as the New Language for Real-World Decision Making. - Sherry Yang 001; Jacob C. Walker; Jack Parker-Holder; Yilun Du; Jake Bruce; André Barreto 001; Pieter Abbeel; Dale Schuurmans (ICML, 2024)

3D-VLA: A 3D Vision-Language-Action Generative World Model. - Haoyu Zhen; Xiaowen Qiu; Peihao Chen; Jincheng Yang; Xin Yan 008; Yilun Du; Yining Hong; Chuang Gan 001 (ICML, 2024)

RoboDreamer: Learning Compositional World Models for Robot Imagination. - Siyuan Zhou; Yilun Du; Jiaben Chen; Yandong Li; Dit-Yan Yeung; Chuang Gan 001 (ICML, 2024)

Disentangled Acoustic Fields For Multimodal Physical Scene Understanding. - Jie Yin; Andrew Luo; Yilun Du; Anoop Cherian; Tim K. Marks; Jonathan Le Roux; Chuang Gan 001 (IROS, 2024)

Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion. - Boyuan Chen 003; Diego Marti Monso; Yilun Du; Max Simchowitz; Russ Tedrake; Vincent Sitzmann (NeurIPS, 2024)

Few-Shot Task Learning through Inverse Generative Modeling. - Aviv Netanyahu; Yilun Du; Antonia Bronars; Jyothish Pari; Josh Tenenbaum 001; Tianmin Shu; Pulkit Agrawal 001 (NeurIPS, 2024)

PoCo: Policy Composition from and for Heterogeneous Robot Learning. - Lirui Wang; Jialiang Zhao; Yilun Du; Edward H. Adelson; Russ Tedrake (Robotics: Science and Systems, 2024)

Set It Up!: Functional Object Arrangement with Compositional Generative Models. - Yiqing Xu; Jiayuan Mao; Yilun Du; Tomás Lozano-Pérez; Leslie Pack Kaelbling; David Hsu (Robotics: Science and Systems, 2024)

Compositional Generative Modeling: A Single Model is Not All You Need. - Yilun Du; Leslie Pack Kaelbling (CoRR, 2024)

Bridging Associative Memory and Probabilistic Modeling. - Rylan Schaeffer; Nika Zahedi; Mikail Khona; Dhruv Pai; Sang T. Truong; Yilun Du; Mitchell Ostrow; Sarthak Chandra; Andres Carranza; Ila Rani Fiete; Andrey Gromov; Sanmi Koyejo (CoRR, 2024)

Video as the New Language for Real-World Decision Making. - Sherry Yang 001; Jacob C. Walker; Jack Parker-Holder; Yilun Du; Jake Bruce; André Barreto 001; Pieter Abbeel; Dale Schuurmans (CoRR, 2024)

COMBO: Compositional World Models for Embodied Multi-Agent Cooperation. - Hongxin Zhang; Zeyuan Wang; Qiushi Lyu; Zheyuan Zhang; Sunli Chen; Tianmin Shu; Yilun Du; Chuang Gan 001 (CoRR, 2024)

Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations. - Julen Urain; Ajay Mandlekar; Yilun Du; Mahi Shafiullah; Danfei Xu; Katerina Fragkiadaki; Georgia Chalvatzaki; Jan Peters 001 (CoRR, 2024)

Compositional Diffusion Models for Powered Descent Trajectory Generation with Flexible Constraints. - Julia Briden; Yilun Du; Enrico M. Zucchelli; Richard Linares (CoRR, 2024)

Inference-Time Policy Steering through Human Interactions. - Yanwei Wang; Lirui Wang; Yilun Du; Balakumar Sundaralingam; Xuning Yang; Yu-Wei Chao; Claudia Pérez-D'Arpino; Dieter Fox; Julie Shah (CoRR, 2024)

SnapMem: Snapshot-based 3D Scene Memory for Embodied Exploration and Reasoning. - Yuncong Yang; Han Yang; Jiachen Zhou 003; Peihao Chen; Hongxin Zhang; Yilun Du; Chuang Gan 001 (CoRR, 2024)

3D-Mem: 3D Scene Memory for Embodied Exploration and Reasoning. - Yuncong Yang; Han Yang; Jiachen Zhou 003; Peihao Chen; Hongxin Zhang; Yilun Du; Chuang Gan 001 (CVPR, 2025)

AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark. - Wenhao Chai; Enxin Song; Yilun Du; Chenlin Meng; Vashisht Madhavan; Omer Bar-Tal; Jenq-Neng Hwang; Saining Xie; Christopher D. Manning (ICLR, 2025)

Looped Transformers for Length Generalization. - Ying Fan; Yilun Du; Kannan Ramchandran; Kangwook Lee 001 (ICLR, 2025)

Grounding Video Models to Actions through Goal Conditioned Exploration. - Yunhao Luo 001; Yilun Du (ICLR, 2025)

Solving New Tasks by Adapting Internet Video Knowledge. - Calvin Luo; Zilai Zeng; Yilun Du; Chen Sun 002 (ICLR, 2025)

Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains. - Vighnesh Subramaniam; Yilun Du; Joshua B. Tenenbaum; Antonio Torralba 001; Shuang Li 013; Igor Mordatch (ICLR, 2025)

COMBO: Compositional World Models for Embodied Multi-Agent Cooperation. - Hongxin Zhang; Zeyuan Wang; Qiushi Lyu; Zheyuan Zhang; Sunli Chen; Tianmin Shu; Behzad Dariush; Kwonjoon Lee; Yilun Du; Chuang Gan 001 (ICLR, 2025)

Generative AI in Embodied Systems: System-Level Analysis of Performance, Efficiency and Scalability. - Zishen Wan; Jiayi Qian; Yuhang Du; Jason Jabbour; Yilun Du; Yang Zhao 013; Arijit Raychowdhury; Tushar Krishna; Vijay Janapa Reddi (ISPASS, 2025)

Towards Generalist Robot Learning from Internet Video: A Survey. - Robert McCarthy; Daniel Chee Hian Tan; Dominik Schmidt; Fernando Acero; Nathan Herr; Yilun Du; Thomas George Thuruthel; Zhibin Li 001 (J. Artif. Intell. Res., 2025)

Strengthening Generative Robot Policies through Predictive World Modeling. - Han Qi; Haocheng Yin; Yilun Du; Heng Yang (CoRR, 2025)

History-Guided Video Diffusion. - Kiwhan Song; Boyuan Chen 003; Max Simchowitz; Yilun Du; Russ Tedrake; Vincent Sitzmann (CoRR, 2025)

Multi-Agent Verification: Scaling Test-Time Compute with Multiple Verifiers. - Shalev Lifshitz; Sheila A. McIlraith; Yilun Du (CoRR, 2025)

Generative Trajectory Stitching through Diffusion Composition. - Yunhao Luo 001; Utkarsh A. Mishra; Yilun Du; Danfei Xu (CoRR, 2025)

MoE-Loco: Mixture of Experts for Multitask Locomotion. - Runhan Huang; Shaoting Zhu; Yilun Du; Hang Zhao (CoRR, 2025)

AdaWorld: Learning Adaptable World Models with Latent Actions. - Shenyuan Gao; Siyuan Zhou; Yilun Du; Jun Zhang; Chuang Gan 001 (CoRR, 2025)

Gemini Robotics: Bringing AI into the Physical World. - Gemini Robotics Team; Saminda Abeyruwan; Joshua Ainslie; Jean-Baptiste Alayrac; Montserrat Gonzalez Arenas; Travis Armstrong; Ashwin Balakrishna; Robert Baruch; Maria Bauzá 001; Michiel Blokzijl; Steven Bohez; Konstantinos Bousmalis; et al. (CoRR, 2025)

Image-Editing Specialists: An RLAIF Approach for Diffusion Models. - Elior Benarous; Yilun Du; Heng Yang (CoRR, 2025)

Towards Understanding Camera Motions in Any Video. - Zhiqiu Lin; Siyuan Cen; Daniel Jiang; Jay Karhade; Hewei Wang 001; Chancharik Mitra; Tiffany Ling; Yuhan Huang; Sifan Liu; Mingyu Chen; Rushikesh Zawar; Xue Bai; et al. (CoRR, 2025)

TesserAct: Learning 4D Embodied World Models. - Haoyu Zhen; Qiao Sun; Hongxin Zhang; Junyan Li; Siyuan Zhou; Yilun Du; Chuang Gan 001 (CoRR, 2025)

Learning 3D Persistent Embodied World Models. - Siyuan Zhou; Yilun Du; Yuncong Yang; Lei Han; Peihao Chen; Dit-Yan Yeung; Chuang Gan 001 (CoRR, 2025)

Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models. - Louis Béthune; David Vigouroux; Yilun Du; Rufin VanRullen; Thomas Serre; Victor Boutin (CoRR, 2025)

Win Fast or Lose Slow: Balancing Speed and Accuracy in Latency-Sensitive Decisions of LLMs. - Hao Kang; Qingru Zhang; Han Cai; Weiyuan Xu; Tushar Krishna; Yilun Du; Tsachy Weissman (CoRR, 2025)

Compositional Scene Understanding through Inverse Generative Modeling. - Yanbo Wang; Justin Dauwels; Yilun Du (CoRR, 2025)

Anomalies by Synthesis: Anomaly Detection using Generative Diffusion Models for Off-Road Navigation. - Siddharth Ancha; Sunshine Jiang; Travis Manderson; Laura Brandt; Yilun Du; Philip R. Osteen; Nicholas Roy (CoRR, 2025)

Toward Memory-Aided World Models: Benchmarking via Spatial Consistency. - Kewei Lian; Shaofei Cai; Yilun Du; Yitao Liang (CoRR, 2025)

Inference-time Scaling of Diffusion Models through Classical Search. - Xiangcheng Zhang; Haowei Lin; Haotian Ye; James Y. Zou; Jianzhu Ma; Yitao Liang; Yilun Du (CoRR, 2025)

Self-Adapting Improvement Loops for Robotic Learning. - Calvin Luo; Zilai Zeng; Mingxi Jia; Yilun Du; Chen Sun 002 (CoRR, 2025)

Product of Experts for Visual Generation. - Yunzhi Zhang; Carson Murtuza-Lanier; Zizhang Li; Yilun Du; Jiajun Wu 001 (CoRR, 2025)

EvoLM: In Search of Lost Language Model Training Dynamics. - Zhenting Qi; Fan Nie; Alexandre Alahi; James Zou 001; Himabindu Lakkaraju; Yilun Du; Eric P. Xing; Sham M. Kakade; Hanlin Zhang 002 (CoRR, 2025)

Energy-Based Transformers are Scalable Learners and Thinkers. - Alexi Gladstone; Ganesh Nanduru; Md Mofijul Islam; Peixuan Han; Hyeonjeong Ha; Aman Chadha; Yilun Du; Heng Ji 001; Jundong Li; Tariq Iqbal (CoRR, 2025)

Rapid and Safe Trajectory Planning over Diverse Scenes through Diffusion Composition. - Wule Mao; Zhouheng Li; Yunhao Luo 006; Yilun Du; Lei Xie (CoRR, 2025)

MindJourney: Test-Time Scaling with World Models for Spatial Reasoning. - Yuncong Yang; Jiageng Liu; Zheyuan Zhang; Siyuan Zhou; Reuben Tan; Jianwei Yang; Yilun Du; Chuang Gan 001 (CoRR, 2025)

"Set It Up": Functional Object Arrangement with Compositional Generative Models (Journal Version). - Yiqing Xu; Jiayuan Mao; Linfeng Li; Yilun Du; Tomás Lozano-Pérez; Leslie Pack Kaelbling; David Hsu (CoRR, 2025)