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

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

collaborators

13 papers

cs.LG2026

MARCO: Multi-Round Agentic Reinforcement for Conditional Molecular Optimization

Shicheng Fang, Yuxin Wang, Zhuo Yang +6

Molecular optimization is inherently iterative: a candidate is proposed, evaluated against several objectives, and revised while preserving a relationship to the source molecule. M…

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.LG2026

ABOPD: Antibody CDR Design via On-Policy Distillation

Zhuo Yang, Jiaying He, Jiaqing Xie +5

Antibodies are essential therapeutic molecules, and their complementarity-determining regions (CDRs) form the primary antigen-recognition interface. Recent protein generative model…

cs.CL2026

Rethinking Scientific Discovery in the Agentic Era

Yining Zheng, Yuxin Wang, Jiahao Lu +27

Artificial intelligence has advanced scientific discovery, but most AI4Science systems remain fragmented tools that rely on humans to coordinate problem formulation, literature gro…

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.CL2026

Compute Allocation for Self-Evolving LLMs: From Depth-Breadth to Multi-Armed Bandits

Sixue Xing, Haoyu He, Kerui Wu +4

LLM-guided evolutionary search (Evolve systems) has reached state-of-the-art results on mathematical and combinatorial tasks, yet most existing systems report only the best of many…

physics.chem-ph2026★ 1 cited

NMRTrans: Structure Elucidation from Experimental NMR Spectra via Set Transformers

Liujia Yang, Zhuo Yang, Jiaqing Xie +9

Nuclear Magnetic Resonance (NMR) spectroscopy is fundamental for molecular structure elucidation, yet interpreting spectra at scale remains time-consuming and highly expertise-depe…

cs.CE2026

NMRGym: A Comprehensive Benchmark for Nuclear Magnetic Resonance Based Molecular Structure Elucidation

Zheng Fang, Chen Yang, Hai-tao Yu +5

Nuclear Magnetic Resonance (NMR) spectroscopy is the cornerstone of small-molecule structure elucidation. While deep learning has demonstrated significant potential in automating s…

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.LG2025★ 1 cited

SpectrumWorld: Artificial Intelligence Foundation for Spectroscopy

Zhuo Yang, Jiaqing Xie, Shuaike Shen +13

Deep learning holds immense promise for spectroscopy, yet research and evaluation in this emerging field often lack standardized formulations. To address this issue, we introduce S…

cs.LG2025★ 2 cited

SpecMol: A Spectroscopy-Grounded Foundation Model for Multi-Task Molecular Learning

Shuaike Shen, Jiaqing Xie, Zhuo Yang +6

Large language models have emerged as transformative tools in molecular science, demonstrating remarkable potential in molecular property prediction and de novo molecular design. H…

cs.AI2025★ 3 cited

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★ 1 cited

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…