2 citations · 2 across the 1 of their papers we have counts for
9 papers
BioMamba: Domain-Adaptive Biomedical Language Models
Ling Yue, Mingzhi Zhu, Sixue Xing +8
Background. Biomedical language models should improve performance on biomedical text while retaining general-language-modeling fluency. For Mamba-based models, this trade-off has n…
BenchGuard: Who Guards the Benchmarks? Automated Auditing of LLM Agent Benchmarks
Xinming Tu, Tianze Wang, Yingzhou +4
As benchmarks grow in complexity, many apparent agent failures are not failures of the agent at all - they are failures of the benchmark itself: broken specifications, implicit ass…
SMILES-Mamba: Chemical Mamba Foundation Models for Drug ADMET Prediction
Bohao Xu, Yingzhou Lu, Chenhao Li +5
In drug discovery, predicting the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of small-molecule drugs is critical for ensuring safety and effic…
Beyond Affinity: A Benchmark of 1D, 2D, and 3D Methods Reveals Critical Trade-offs in Structure-Based Drug Design
Kangyu Zheng, Kai Zhang, Jiale Tan +7
Currently, the field of structure-based drug design is dominated by three main types of algorithms: search-based algorithms, deep generative models, and reinforcement learning. Whi…
Foundation Model in Biomedicine
Xiangrui Liu, Yuanyuan Zhang, Qianyu Shang +14
Foundation models, first introduced in 2021, refer to large-scale pretrained models (e.g., large language models (LLMs) and vision-language models (VLMs)) that learn from extensive…
Gradient GA: Gradient Genetic Algorithm for Drug Molecular Design
Chris Zhuang, Debadyuti Mukherjee, Yingzhou Lu +2
Molecular discovery has brought great benefits to the chemical industry. Various molecule design techniques are developed to identify molecules with desirable properties. Tradition…