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20242026
most citedMOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses

5 citations · 15 across the 12 of their papers we have counts for

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cs.LG2026

Disagree to Accelerate: Closing the Loop on Diffusion Feature Forecasts

Yanchao Li, Jiaqing Xie, Ben Gao +6

Training-free feature forecasting accelerates diffusion sampling by predicting features at skipped denoising steps. Recent work has mainly focused on designing stronger forecasters…

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.LG2025★ 1 cited

ChemBOMAS: Accelerated BO in Chemistry with LLM-Enhanced Multi-Agent System

Dong Han, Zhehong Ai, Pengxiang Cai +16

Bayesian optimization (BO) is a powerful tool for scientific discovery in chemistry, yet its efficiency is often hampered by the sparse experimental data and vast search space. Her…

cs.LG2025

Intern-S1: A Scientific Multimodal Foundation Model

Lei Bai, Zhongrui Cai, Yuhang Cao +173

In recent years, a plethora of open-source foundation models have emerged, achieving remarkable progress in some widely attended fields, with performance being quite close to that…