Papers by Kaifeng Liu
MARS2: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code Generation (2026.acl-long)
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Pengfei Li, Shijie Wang, Fangyuan Li, Yikun Fu, Kaifeng Liu, Kaiyan Zhang, Dazhi Zhang, Yuqiang Li, Biqing Qi, Bowen Zhou
| Challenge: | Existing approaches to reinforcement learning are decoupled from structured search due to limited trajectory diversity. |
| Approach: | They propose a unified RL framework that integrates multiple agents within a shared tree-structured search environment. |
| Outcome: | Experiments show that MARS2 improves performance across diverse model combinations and training settings. |
FAER: Benchmarking VLMs for Failure-Aware Embodied Reasoning (2026.findings-acl)
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| Challenge: | Visual-language models (VLMs) are the core component of embodied agents in perceiving the environment and making decisions. |
| Approach: | They propose a failure-aware benchmark to evaluate the performance of visual language models (VLMs) in long-horizon tasks. |
| Outcome: | The proposed benchmark evaluates the performance of 16 widely utilized VLMs and 4 LLMs for FAER tasks. |