2 citations · 5 across the 15 of their papers we have counts for
6 papers · 1 filter
Principles that Guide, Actions that Inform: Agent Evolution via Knowledge Abstraction
Bowen Ye, Yongchao Xu, Junkai Ma +2
Large language model (LLM) agents have demonstrated strong capabilities in interactive environments, yet their ability to continually evolve from experience remains limited. Althou…
Auditing Action Settlement in LLM Agent Environments: Order, Progress, and Replay
Haotian Chen, Bowen Ye, Yuning Zhang +1
Concurrent actions in large language model (LLM) agent environments require arbitration even when each proposal is individually valid. We implement a typed snapshot-settlement cont…
CodeMidas: Scaling Agentic Coding RL Environments from Code Itself
Bowen Ye, Lei Li, Shicheng Li +16
Training capable coding agents via reinforcement learning (RL) requires diverse tasks with reliable verifiers. Open-source codebases offer a rich source of such tasks, while existi…
CoEvo-Mem: Co-Evolving Retrieval Policy and Memory Bank for LLM Agents
Bowen Ye, Yongchao Xu, Zhijian Li +3
As memories accumulate across tasks and sessions, the performance of long-term LLM agents depends jointly on query-specific retrieval and continual memory refinement. However, exis…
ReasonSTL: Bridging Natural Language and Signal Temporal Logic via Tool-Augmented Process-Rewarded Learning
Bowen Ye, Zhijian Li, Junyue Huang +2
Signal Temporal Logic (STL) is an expressive formal language for specifying spatio-temporal requirements over real-valued, real-time signals. It has been widely used for the verifi…
Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents
Bowen Ye, Rang Li, Qibin Yang +10
Large language models are increasingly deployed as autonomous agents for multi-step workflows in real-world software environments. However, existing agent benchmarks are limited by…