News
| Jul 27, 2025 | Excited to have our paper “CrafText Benchmark: Advancing Instruction Following in Complex Multimodal Open-Ended World” in the Main Track at ACL 2025 in Vienna! We introduce CrafText, a new benchmark and environment for multimodal RL, designed to tackle instruction following in complex, dynamic settings. The paper also proposes several strong baselines to drive progress in this area. Here are the links to the paper |
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| Apr 18, 2025 | Excited to share that our paper, IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents, has been accepted to SIGIR! It’s a great conclusion to the series of IGLU competitions. Read it on arXiv |
| Jan 23, 2025 | I’m happy to share that our paper, POGEMA: A Benchmark Platform for Cooperative Multi-Agent Pathfinding, has been accepted to the ICLR-2025 Conference! Here are the links to the preprint on arXiv and the openreview. |
| Dec 10, 2024 | I’m happy to announce that our paper, MAPF-GPT: Imitation Learning for Multi-Agent Pathfinding at Scale, has been accepted to the AAAI 2025 Conference! Here are the links to the preprint on arXiv and the open-source code. |
| Sep 05, 2024 | I’m excited to announce our recent preprint titled MAPF-GPT, a GPT-like model designed for MAPF problems. It is trained using pure imitation learning on trajectories generated by LaCAM. MAPF-GPT performs exceptionally well on unseen instances and outperforms state-of-the-art learnable solvers such as SCRIMP and DCC. Here are the links to the preprint on arXiv and the open-source code. |
| Jul 15, 2024 | Happy to announce that our paper Instruction Following with Goal-Conditioned Reinforcement Learning in Virtual Environments has been accepted to ECAI 2024, arxiv. |
| Jan 18, 2024 | I’m thrilled to announce that two of my submissions to AAAI 2024 have been accepted. The paper titled “Learning to Follow: Lifelong Multi-agent Pathfinding with Decentralized Replanning” will be presented as an oral presentation, and the paper “Decentralized Monte Carlo Tree Search for Partially Observable Multi-agent Pathfinding” will be showcased in a poster session. |