46 citations · 66 across the 11 of their papers we have counts for
12 papers
Building a physics-aware AI ecosystem for solid-state hydrogen storage materials
Seong-Hoon Jang, Yiwen Yao, Chuanyu Liu +66
Hydrogen storage remains a central bottleneck for scalable hydrogen energy systems due to the multiscale and coupled nature of the thermodynamics, kinetics, and microstructural evo…
CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics
Weida Wang, Dongchen Huang, Jiatong Li +32
We introduce CMPhysBench, designed to assess the proficiency of Large Language Models (LLMs) in Condensed Matter Physics, as a novel Benchmark. CMPhysBench is composed of more than…
SELT: Self-Evaluation Tree Search for LLMs with Task Decomposition
Mengsong Wu, Di Zhang, Yuqiang Li +2
While Large Language Models (LLMs) have achieved remarkable success in a wide range of applications, their performance often degrades in complex reasoning tasks. In this work, we i…
Control-R: Towards controllable test-time scaling
Di Zhang, Weida Wang, Junxian Li +10
This paper target in addressing the challenges of underthinking and overthinking in long chain-of-thought (CoT) reasoning for Large Reasoning Models (LRMs) by introducing Reasoning…
MOOSE-Chem3: Toward Experiment-Guided Hypothesis Ranking via Simulated Experimental Feedback
Wanhao Liu, Zonglin Yang, Jue Wang +7
Hypothesis ranking is vital for automated scientific discovery, especially in cost-intensive, throughput-limited natural science domains. Current methods focus on pre-experiment ra…
Biology-Instructions: A Dataset and Benchmark for Multi-Omics Sequence Understanding Capability of Large Language Models
Haonan He, Yuchen Ren, Yining Tang +12
Large language models (LLMs) have shown remarkable capabilities in general domains, but their application to multi-omics biology remains underexplored. To address this gap, we intr…
LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning
Di Zhang, Jianbo Wu, Jingdi Lei +9
This paper presents an advanced mathematical problem-solving framework, LLaMA-Berry, for enhancing the mathematical reasoning ability of Large Language Models (LLMs). The framework…
Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoning
Di Zhang, Junxian Li, Jingdi Lei +10
Vision-language models (VLMs) have shown remarkable advancements in multimodal reasoning tasks. However, they still often generate inaccurate or irrelevant responses due to issues…
MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts
Jiatong Li, Yunqing Liu, Wei Liu +6
Molecule discovery is a pivotal research field, impacting everything from medicine to materials. Recently, Large Language Models (LLMs) have been widely adopted in molecular unders…
ChemVLM: Exploring the Power of Multimodal Large Language Models in Chemistry Area
Junxian Li, Di Zhang, Xunzhi Wang +16
Large Language Models (LLMs) have achieved remarkable success and have been applied across various scientific fields, including chemistry. However, many chemical tasks require the…
Accessing GPT-4 level Mathematical Olympiad Solutions via Monte Carlo Tree Self-refine with LLaMa-3 8B
Di Zhang, Xiaoshui Huang, Dongzhan Zhou +2
This paper introduces the MCT Self-Refine (MCTSr) algorithm, an innovative integration of Large Language Models (LLMs) with Monte Carlo Tree Search (MCTS), designed to enhance perf…
ChemLLM: A Chemical Large Language Model
Di Zhang, Wei Liu, Qian Tan +12
Large language models (LLMs) have made impressive progress in chemistry applications. However, the community lacks an LLM specifically designed for chemistry. The main challenges a…