3 citations · 7 across the 4 of their papers we have counts for
5 papers
Func-R1: Incentivizing Mathematical Function Reasoning in Multimodal Large Language Models
Mingze Yin, Xiaohan Wang, Dian Li +8
Performing deliberate mathematical reasoning in visual contexts is a hallmark of advanced Multimodal Large Language Models (MLLMs) and requires a sophisticated synthesis of percept…
BioMatrix: Towards a Comprehensive Biological Foundation Model Spanning the Modality Matrix of Sequences, Structures, and Language
Qizhi Pei, Zhimeng Zhou, Yi Duan +9
We present BioMatrix, the first multimodal foundation model that natively integrates sequences, structures, and natural language for both molecules and proteins within a single dec…
Evaluating Large Language Models in Scientific Discovery
Zhangde Song, Jieyu Lu, Yuanqi Du +53
Large language models (LLMs) are increasingly applied to scientific research, yet prevailing science benchmarks probe decontextualized knowledge and overlook the iterative reasonin…
Token-Mol 1.0: Tokenized drug design with large language model
Jike Wang, Rui Qin, Mingyang Wang +17
Significant interests have recently risen in leveraging sequence-based large language models (LLMs) for drug design. However, most current applications of LLMs in drug discovery la…
Human-level molecular optimization driven by mol-gene evolution
Jiebin Fang, Churu Mao, Yuchen Zhu +3
De novo molecule generation allows the search for more drug-like hits across a vast chemical space. However, lead optimization is still required, and the process of optimizing mole…