most citedTowards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models

18 citations · 19 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CY2025

OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists

Chenyang Shao, Dehao Huang, Yu Li +18

With the rapid development of Large Language Models (LLMs), AI agents have demonstrated increasing proficiency in scientific tasks, ranging from hypothesis generation and experimen…

q-bio.NC2025

AI Agent Behavioral Science

Lin Chen, Yunke Zhang, Jie Feng +13

Recent advances in large language models (LLMs) have enabled the development of AI agents that exhibit increasingly human-like behaviors, including planning, adaptation, and social…

cs.CL2025

AgentSwift: Efficient LLM Agent Design via Value-guided Hierarchical Search

Yu Li, Lehui Li, Zhihao Wu +5

Large language model (LLM) agents have demonstrated strong capabilities across diverse domains, yet automated agent design remains a significant challenge. Current automated agent…

cs.IR20251 cited

XPath Agent: An Efficient XPath Programming Agent Based on LLM for Web Crawler

Yu Li, Bryce Wang, Xinyu Luan

We present XPath Agent, a production-ready XPath programming agent specifically designed for web crawling and web GUI testing. A key feature of XPath Agent is its ability to automa…

cs.AI202518 cited

Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models

Fengli Xu, Qianyue Hao, Zefang Zong +17

Language has long been conceived as an essential tool for human reasoning. The breakthrough of Large Language Models (LLMs) has sparked significant research interest in leveraging…