most citedQCBench: Evaluating Large Language Models on Domain-Specific Quantitative Chemistry

3 citations · 8 across the 12 of their papers we have counts for

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cs.AI2026

AgentFold: Closed-Loop Agentic Search for Protein Folding Model Design

Mingquan Liu, Jiangyu Chen, Hanqun Cao +9

Scientific LLM agents have shown promise in literature reasoning, tool use, and experiment planning, but it remains unclear whether they can autonomously improve large, tightly cou…

cs.AI2026

OmniMatBench: A Human-Calibrated Multimodal Reasoning Benchmark Across 19 Materials Science Subfields

Wanhao Liu, Jiaqing Xie, Qian Tan +10

As multimodal language models play an increasingly important role in scientific research, materials science offers a critical testbed due to its interdisciplinary, multimodal, and…

cs.AI2025

MolAct: An Agentic RL Framework for Molecular Editing and Property Optimization

Zhuo Yang, Yeyun Chen, Jiaqing Xie +7

Molecular editing and optimization are multi-step problems that require iteratively improving properties while keeping molecules chemically valid and structurally similar. We frame…

cs.AI2025

QCBench: Evaluating Large Language Models on Domain-Specific Quantitative Chemistry

Jiaqing Xie, Weida Wang, Ben Gao +5

Quantitative chemistry is central to modern chemical research, yet the ability of large language models (LLMs) to perform its rigorous, step-by-step calculations remains underexplo…

cs.AI2025

Reasoning BO: Enhancing Bayesian Optimization with Long-Context Reasoning Power of LLMs

Zhuo Yang, Daolang Wang, Lingli Ge +3

Many real-world scientific and industrial applications require the optimization of expensive black-box functions. Bayesian Optimization (BO) provides an effective framework for suc…