3 citations · 5 across the 3 of their papers we have counts for
4 papers
HarnessTTT: Learn to Optimize Harness at Test-Time for Scientific Discovery
Yingzi Ma, Yulong Cao, Nanxi Li +5
Scientific discovery with language models requires finding the best valid solution within a finite computational budget. We study how feedback from this search can improve the proc…
L^2M^3OF: A Large Language Multimodal Model for Metal-Organic Frameworks
Jiyu Cui, Fang Wu, Haokai Zhao +4
Large language models have demonstrated remarkable reasoning capabilities across diverse natural language tasks. However, comparable breakthroughs in scientific discovery are more…
When to Trust Context: Self-Reflective Debates for Context Reliability
Zeqi Zhou, Fang Wu, Shayan Talaei +5
Large language models frequently encounter conflicts between their parametric knowledge and contextual input, often resulting in factual inconsistencies or hallucinations. We propo…
PoseX: AI Defeats Physics Approaches on Protein-Ligand Cross Docking
Yize Jiang, Xinze Li, Yuanyuan Zhang +13
Existing protein-ligand docking studies typically focus on the self-docking scenario, which is less practical in real applications. Moreover, some studies involve heavy frameworks…