Kolobov, Andrey

31 publications

ICLR 2025 Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning Patrick Yin, Tyler Westenbroek, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta

ICCV 2025 SITE: Towards Spatial Intelligence Thorough Evaluation Wenqi Wang, Reuben Tan, Pengyue Zhu, Jianwei Yang, Zhengyuan Yang, Lijuan Wang, Andrey Kolobov, Jianfeng Gao, Boqing Gong

ICLR 2025 TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies Ruijie Zheng, Yongyuan Liang, Shuaiyi Huang, Jianfeng Gao, Hal Daumé Iii, Andrey Kolobov, Furong Huang, Jianwei Yang

ICLR 2024 Improving Offline RL by Blending Heuristics Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng

ICLRW 2024 LLF-Bench: Benchmark for Interactive Learning from Language Feedback Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan

ICML 2024 PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control Ruijie Zheng, Ching-An Cheng, Hal Daumé Iii, Furong Huang, Andrey Kolobov

CoRL 2023 Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control Vivek Myers, Andre Wang He, Kuan Fang, Homer Rich Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca Dragan, Sergey Levine

NeurIPSW 2023 Importance of Directional Feedback for LLM-Based Optimizers Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan

CoRL 2023 PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov

NeurIPS 2023 Survival Instinct in Offline Reinforcement Learning Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng

ICMLW 2023 Survival Instinct in Offline Reinforcement Learning and Implicit Human Bias in Data Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng

ICLR 2022 Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL Bogdan Mazoure, Ahmed M Ahmed, R Devon Hjelm, Andrey Kolobov, Patrick MacAlpine

NeurIPS 2022 MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew Hausknecht

NeurIPS 2021 Heuristic-Guided Reinforcement Learning Ching-An Cheng, Andrey Kolobov, Adith Swaminathan

CoRL 2020 MultiPoint: Cross-Spectral Registration of Thermal and Optical Aerial Imagery Florian Achermann, Andrey Kolobov, Debadeepta Dey, Timo Hinzmann, Jen Jen Chung, Roland Siegwart, Nicholas Lawrance

ICML 2020 Online Learning for Active Cache Synchronization Andrey Kolobov, Sebastien Bubeck, Julian Zimmert

NeurIPS 2020 Policy Improvement via Imitation of Multiple Oracles Ching-An Cheng, Andrey Kolobov, Alekh Agarwal

NeurIPS 2020 Safe Reinforcement Learning via Curriculum Induction Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal

NeurIPS 2019 Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling Andrey Kolobov, Yuval Peres, Cheng Lu, Eric J Horvitz

ICMLW 2019 Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling Andrey Kolobov, Yuval Peres, Cheng Lu, Eric Horvitz

IJCAI 2016 Interactive Teaching Strategies for Agent Training Ofra Amir, Ece Kamar, Andrey Kolobov, Barbara J. Grosz

IJCAI 2015 Metareasoning for Planning Under Uncertainty Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz

AAAI 2015 TODTLER: Two-Order-Deep Transfer Learning Jan Van Haaren, Andrey Kolobov, Jesse Davis

AAAI 2014 Saturated Path-Constrained MDP: Planning Under Uncertainty and Deterministic Model-Checking Constraints Jonathan Sprauel, Andrey Kolobov, Florent Teichteil-Königsbuch

UAI 2012 A Theory of Goal-Oriented MDPs with Dead Ends Andrey Kolobov, Mausam, Daniel S. Weld

AAAI 2012 LRTDP Versus UCT for Online Probabilistic Planning Andrey Kolobov, Mausam, Daniel S. Weld

IJCAI 2011 Towards Scalable MDP Algorithms Andrey Kolobov, Mausam, Daniel S. Weld

AAAI 2010 SixthSense: Fast and Reliable Recognition of Dead Ends in MDPs Andrey Kolobov, Mausam, Daniel S. Weld

IJCAI 2009 ReTrASE: Integrating Paradigms for Approximate Probabilistic Planning Andrey Kolobov, Mausam, Daniel S. Weld

AISTATS 2005 Approximate Inference for Infinite Contingent Bayesian Networks Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong, Andrey Kolobov

IJCAI 2005 BLOG: Probabilistic Models with Unknown Objects Brian Milch, Bhaskara Marthi, Stuart Russell, David A. Sontag, Daniel L. Ong, Andrey Kolobov