collaborators

17 papers

cs.AI2026

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods

Hai Xia, Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider

Large neighborhood search normally selects a random subset of decision variables for iterative optimization. To efficiently solve various problems, researchers tend to design varia…

cs.AI2026

Science Edge Evaluation: SEE the Missing Step Toward Real Scientific Discovery

Taolin Han, Yuchen Zhang, Jinghang Wang +22

Large language models (LLMs) are increasingly involved in scientific discovery, yet it remains unclear whether they can support complex real laboratory science. Here we introduce S…

cs.CL2026

Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent

Lei Bai, Zongsheng Cao, Yang Chen +50

The paper introduces Agents-A1, a 35B mixture-of-experts agent model that attains trillion-parameter-level performance by extending the length of reasoning horizons and integrating…

cs.LG2026

ResearchClawBench: A Benchmark for End-to-End Autonomous Scientific Research

Wanghan Xu, Shuo Li, Tianlin Ye +48

AI coding agents are increasingly used for scientific work, but their end-to-end autonomous research capability remains difficult to verify. We present ResearchClawBench, a benchma…

cs.AI2026

SCI-PRM: A Tool Aware Process Reward Model for Scientific Reasoning Verification

Xiangyu Zhao, Henry Hengyuan Zhao, Yiheng Wang +7

While Process Reward Models (PRMs) have achieved remarkable success in mathematical reasoning, their application in complex scientific domains-such as biology, chemistry, and physi…

cs.CV2026

NICE FACT: Diagnosing and Calibrating VLMs in Quantitative Reasoning for Kinematic Physics

Jian Lan, Zhicheng Liu, Xinpeng Wang +5

The ability to derive precise spatial and physical insights is a cornerstone of vision-language models (VLMs), yet their poor performances in related spatial intelligence tasks suc…