6 papers · 1 filter
MARS: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code Generation
Pengfei Li, Shijie Wang, Fangyuan Li +7
Reinforcement learning (RL) paradigms have demonstrated strong performance on reasoning-intensive tasks such as code generation. However, limited trajectory diversity often leads t…
OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth?
Xuetian Chen, Yinghao Chen, Xinfeng Yuan +12
Computer-using agents have shown strong potential to boost human productivity and enable new application forms across platforms. While recent advances have led to usable applicatio…
MSI-Agent: Incorporating Multi-Scale Insight into Embodied Agents for Superior Planning and Decision-Making
Dayuan Fu, Biqing Qi, Yihuai Gao +3
Long-term memory is significant for agents, in which insights play a crucial role. However, the emergence of irrelevant insight and the lack of general insight can greatly undermin…
Automating Exploratory Proteomics Research via Language Models
Ning Ding, Shang Qu, Linhai Xie +13
With the development of artificial intelligence, its contribution to science is evolving from simulating a complex problem to automating entire research processes and producing nov…
SR-CIS: Self-Reflective Incremental System with Decoupled Memory and Reasoning
Biqing Qi, Junqi Gao, Xinquan Chen +3
The ability of humans to rapidly learn new knowledge while retaining old memories poses a significant challenge for current deep learning models. To handle this challenge, we draw…
Online DPO: Online Direct Preference Optimization with Fast-Slow Chasing
Biqing Qi, Pengfei Li, Fangyuan Li +3
Direct Preference Optimization (DPO) improves the alignment of large language models (LLMs) with human values by training directly on human preference datasets, eliminating the nee…