Andrey Kolobov

74 papers A* 27A 5B 1Misc 3Journal 32Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Benchmarking Affordance Generalization with BusyBox. CoRR Dean Fortier, Timothy Adamson, Tess Hellebrekers, Teresa LaScala, Kofi Ennin, Michael Murray, Andrey Kolobov, Galen Mullins
2026	J	`jnl`	Emergent Dexterity via Diverse Resets and Large-Scale Reinforcement Learning. CoRR Patrick Yin, Tyler Westenbroek, Zhengyu Zhang, Joshua Tran, Ignacio Dagnino, Eeshani Shilamkar, Numfor Mbiziwo-Tiapo, Simran Bagaria, Xinlei Liu, Galen Mullins, Andrey Kolobov, Abhishek Gupta
2026	J	`jnl`	Latent Policy Steering through One-Step Flow Policies. CoRR Hokyun Im, Andrey Kolobov, Jianlong Fu, Youngwoon Lee
2026	J	`jnl`	Offload or Overload: A Platform Measurement Study of Mobile Robotic Manipulation Workloads. CoRR Sara Pohland, Xenofon Foukas, Ganesh Ananthanarayanan, Andrey Kolobov, Sanjeev Mehrotra, Bozidar Radunovic, Ankit Verma
2025	J	`jnl`	LoLA: Long Horizon Latent Action Learning for General Robot Manipulation. CoRR Xiaofan Wang, Xingyu Gao, Jianlong Fu, Zuolei Li, Dean Fortier, Galen Mullins, Andrey Kolobov, Baining Guo
2025	A*	`conf`	Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning. ICLR Patrick Yin, Tyler Westenbroek, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta
2025	J	`jnl`	SITE: towards Spatial Intelligence Thorough Evaluation. CoRR Wenqi Wang, Reuben Tan, Pengyue Zhu, Jianwei Yang, Zhengyuan Yang, Lijuan Wang, Andrey Kolobov, Jianfeng Gao, Boqing Gong
2025	A*	`conf`	TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies. ICLR Ruijie Zheng, Yongyuan Liang, Shuaiyi Huang, Jianfeng Gao, Hal Daumé III, Andrey Kolobov, Furong Huang, Jianwei Yang
2025	J	`jnl`	TwinVLA: Data-Efficient Bimanual Manipulation with Twin Single-Arm Vision-Language-Action Models. CoRR Hokyun Im, Euijin Jeong, Jianlong Fu, Andrey Kolobov, Youngwoon Lee
2024	A*	`conf`	Improving Offline RL by Blending Heuristics. ICLR Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
2024	A*	`conf`	PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control. ICML Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
2024	J	`jnl`	PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem. CoRR Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
2024	J	`jnl`	The Importance of Directional Feedback for LLM-based Optimizers. CoRR Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
2024	J	`jnl`	TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies. CoRR Ruijie Zheng, Yongyuan Liang, Shuaiyi Huang, Jianfeng Gao, Hal Daumé III, Andrey Kolobov, Furong Huang, Jianwei Yang
2024	A*	`conf`	Watching the Air Rise: Learning-Based Single-Frame Schlieren Detection. ICRA Florian Achermann, Julian Andreas Haug, Tobias Zumsteg, Nicholas R. J. Lawrance, Jen Jen Chung, Andrey Kolobov, Roland Siegwart
2024	J	`jnl`	WindSeer: Real-time volumetric wind prediction over complex terrain aboard a small UAV. CoRR Florian Achermann, Thomas Stastny, Bogdan Danciu, Andrey Kolobov, Jen Jen Chung, Roland Siegwart, Nicholas R. J. Lawrance
2023	A*	`conf`	Exploring Levels of Control for a Navigation Assistant for Blind Travelers. HRI Vinitha Ranganeni, Mike Sinclair, Eyal Ofek, Amos Miller, Jonathan Campbell, Andrey Kolobov, Edward Cutrell
2023	J	`jnl`	Exploring Levels of Control for a Navigation Assistant for Blind Travelers. CoRR Vinitha Ranganeni, Mike Sinclair, Eyal Ofek, Amos Miller, Jonathan Campbell, Andrey Kolobov, Edward Cutrell
2023	Misc	`conf`	Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRL Vivek Myers, Andre Wang He, Kuan Fang, Homer Rich Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine
2023	J	`jnl`	Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRR Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine
2023	J	`jnl`	Improving Offline RL by Blending Heuristics. CoRR Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
2023	J	`jnl`	Influence of Heat Loss on the Chaotic Dynamics of Reaction Waves in the Model with Chain-Branching Reaction. Int. J. Bifurc. Chaos Maxim Kuznetsov, Andrey Kolobov, Vladimir Gubernov, Andrey Polezhaev
2023	J	`jnl`	Interactive Robot Learning from Verbal Correction. CoRR Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
2023	J	`jnl`	LLF-Bench: Benchmark for Interactive Learning from Language Feedback. CoRR Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
2023	Misc	`conf`	PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining. CoRL Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
2023	J	`jnl`	PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining. CoRR Garrett Thomas, Ching-An Cheng, Ricky Loynd, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
2023	A*	`conf`	Survival Instinct in Offline Reinforcement Learning. NeurIPS Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
2023	J	`jnl`	Survival Instinct in Offline Reinforcement Learning. CoRR Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
2022	A*	`conf`	Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL. ICLR Bogdan Mazoure, Ahmed M. Ahmed, R. Devon Hjelm, Andrey Kolobov, Patrick MacAlpine
2022	A*	`conf`	MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. NeurIPS Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht
2022	J	`jnl`	MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. CoRR Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht
2022	J	`jnl`	The Sandbox Environment for Generalizable Agent Research (SEGAR). CoRR R. Devon Hjelm, Bogdan Mazoure, Florian Golemo, Felipe Frujeri, Mihai Jalobeanu, Andrey Kolobov
2021	J	`jnl`	Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL. CoRR Bogdan Mazoure, Ahmed M. Ahmed, Patrick MacAlpine, R. Devon Hjelm, Andrey Kolobov
2021	A*	`conf`	Heuristic-Guided Reinforcement Learning. NeurIPS Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
2021	J	`jnl`	Heuristic-Guided Reinforcement Learning. CoRR Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
2021	J	`jnl`	Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. CoRR Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe
2020	—	`conf`	Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. NeurIPS (Competition and Demos) Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe
2020	Misc	`conf`	MultiPoint: Cross-spectral registration of thermal and optical aerial imagery. CoRL Florian Achermann, Andrey Kolobov, Debadeepta Dey, Timo Hinzmann, Jen Jen Chung, Roland Siegwart, Nicholas R. J. Lawrance
2020	A*	`conf`	Online Learning for Active Cache Synchronization. ICML Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
2020	J	`jnl`	Online Learning for Active Cache Synchronization. CoRR Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
2020	J	`jnl`	Policy Improvement from Multiple Experts. CoRR Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
2020	A*	`conf`	Policy Improvement via Imitation of Multiple Oracles. NeurIPS Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
2020	A*	`conf`	Safe Reinforcement Learning via Curriculum Induction. NeurIPS Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
2020	J	`jnl`	Safe Reinforcement Learning via Curriculum Induction. CoRR Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
2019	A*	`conf`	Optimal Freshness Crawl Under Politeness Constraints. SIGIR Andrey Kolobov, Yuval Peres, Eyal Lubetzky, Eric Horvitz
2019	A*	`conf`	Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling. NeurIPS Andrey Kolobov, Yuval Peres, Cheng Lu, Eric Horvitz
2018	A	`conf`	ArduSoar: An Open-Source Thermalling Controller for Resource-Constrained Autopilots. IROS Samuel Tabor, Iain Guilliard, Andrey Kolobov
2018	J	`jnl`	ArduSoar: an Open-Source Thermalling Controller for Resource-Constrained Autopilots. CoRR Samuel Tabor, Iain Guilliard, Andrey Kolobov
2018	J	`jnl`	Autonomous Thermalling as a Partially Observable Markov Decision Process (Extended Version). CoRR Iain Guilliard, Richard Rogahn, Jim Piavis, Andrey Kolobov
2018	—	`conf`	Autonomous Thermalling as a Partially Observable Markov Decision Process. Robotics: Science and Systems Iain Guilliard, Richard Rogahn, Jim Piavis, Andrey Kolobov
2016	A*	`conf`	Interactive Teaching Strategies for Agent Training. IJCAI Ofra Amir, Ece Kamar, Andrey Kolobov, Barbara J. Grosz
2015	A*	`conf`	Metareasoning for Planning Under Uncertainty. IJCAI Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz
2015	J	`jnl`	Metareasoning for Planning Under Uncertainty. CoRR Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz
2015	A	`conf`	Selecting Robust Strategies in RTS Games via Concurrent Plan Augmentation. AAMAS Abdelrahman Elogeel, Andrey Kolobov, Matthew Alden, Ankur Teredesai
2015	A*	`conf`	TODTLER: Two-Order-Deep Transfer Learning. AAAI Jan Van Haaren, Andrey Kolobov, Jesse Davis
2014	A	`conf`	Gauss meets Canadian traveler: shortest-path problems with correlated natural dynamics. AAMAS Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor
2014	B	`conf`	Parallel Task Routing for Crowdsourcing. HCOMP Jonathan Bragg, Andrey Kolobov, Mausam, Daniel S. Weld
2014	A*	`conf`	Saturated Path-Constrained MDP: Planning under Uncertainty and Deterministic Model-Checking Constraints. AAAI Jonathan Sprauel, Andrey Kolobov, Florent Teichteil-Königsbuch
2013	—	`conf`	Joint Crowdsourcing of Multiple Tasks. HCOMP (Works in Progress / Demos) Andrey Kolobov, Mausam, Daniel S. Weld
2013	—	`—`	Scalable Methods and Expressive Models for Planning Under Uncertainty. Andrey Kolobov
2012	J	`jnl`	A Theory of Goal-Oriented MDPs with Dead Ends CoRR Andrey Kolobov, Mausam, Daniel S. Weld
2012	A	`conf`	A Theory of Goal-Oriented MDPs with Dead Ends. UAI Andrey Kolobov, Mausam, Daniel S. Weld
2012	J	`jnl`	Discovering hidden structure in factored MDPs. Artif. Intell. Andrey Kolobov, Mausam, Daniel S. Weld
2012	A*	`conf`	LRTDP Versus UCT for Online Probabilistic Planning. AAAI Andrey Kolobov, Mausam, Daniel S. Weld
2012	—	`book`	Planning with Markov Decision Processes: An AI Perspective Planning with Markov Decision Processes Mausam, Andrey Kolobov
2012	A*	`conf`	Reverse Iterative Deepening for Finite-Horizon MDPs with Large Branching Factors. ICAPS Andrey Kolobov, Peng Dai, Mausam, Daniel S. Weld
2011	A*	`conf`	Heuristic Search for Generalized Stochastic Shortest Path MDPs. ICAPS Andrey Kolobov, Mausam, Daniel S. Weld, Hector Geffner
2011	A*	`conf`	Towards Scalable MDP Algorithms. IJCAI Andrey Kolobov, Mausam, Daniel S. Weld
2010	A*	`conf`	Classical Planning in MDP Heuristics: with a Little Help from Generalization. ICAPS Andrey Kolobov, Mausam, Daniel S. Weld
2010	A*	`conf`	SixthSense: Fast and Reliable Recognition of Dead Ends in MDPs. AAAI Andrey Kolobov, Mausam, Daniel S. Weld
2009	A*	`conf`	ReTrASE: Integrating Paradigms for Approximate Probabilistic Planning. IJCAI Andrey Kolobov, Mausam, Daniel S. Weld
2005	A	`conf`	Approximate Inference for Infinite Contingent Bayesian Networks. AISTATS Brian Milch, Bhaskara Marthi, David A. Sontag, Stuart Russell, Daniel L. Ong, Andrey Kolobov
2005	—	`conf`	BLOG: Probabilistic Models with Unknown Objects. Probabilistic, Logical and Relational Learning Brian Milch, Bhaskara Marthi, Stuart Russell, David A. Sontag, Daniel L. Ong, Andrey Kolobov
2005	A*	`conf`	BLOG: Probabilistic Models with Unknown Objects. IJCAI Brian Milch, Bhaskara Marthi, Stuart Russell, David A. Sontag, Daniel L. Ong, Andrey Kolobov