9 citations · 13 across the 8 of their papers we have counts for
9 papers
Speaking the Language of Science: Toward a General-Purpose Generative Foundation Model for the Natural Sciences
Mingyang Li, Yurou Liu, Jieping Ye +3
In this report, we present LOGOS (Language Of Generative Objects in Science), a scientific generative language model that unifies heterogeneous tasks across the natural sciences wi…
Vectorized Bayesian Inference for Latent Dirichlet-Tree Allocation
Zheng Wang, Nizar Bouguila
Latent Dirichlet Allocation (LDA) is a foundational model for discovering latent thematic structure in discrete data, but its Dirichlet prior cannot represent the rich correlations…
Controlling Thinking Speed in Reasoning Models
Zhengkai Lin, Zhihang Fu, Ze Chen +6
Human cognition is theorized to operate in two modes: fast, intuitive System 1 thinking and slow, deliberate System 2 thinking. While current Large Reasoning Models (LRMs) excel at…
A Generalist Cross-Domain Molecular Learning Framework for Structure-Based Drug Discovery
Yiheng Zhu, Mingyang Li, Junlong Liu +7
Structure-based drug discovery (SBDD) is a systematic scientific process that develops new drugs by leveraging the detailed physical structure of the target protein. Recent advance…
GENERator: A Long-Context Generative Genomic Foundation Model
Wei Wu, Qiuyi Li, Yuanyuan Zhang +15
The rapid advancement of DNA sequencing has produced vast genomic datasets, yet interpreting and engineering genomic function remain fundamental challenges. Recent large language m…
ProtCLIP: Function-Informed Protein Multi-Modal Learning
Hanjing Zhou, Mingze Yin, Wei Wu +5
Multi-modality pre-training paradigm that aligns protein sequences and biological descriptions has learned general protein representations and achieved promising performance in var…
Bridge-IF: Learning Inverse Protein Folding with Markov Bridges
Yiheng Zhu, Jialu Wu, Qiuyi Li +7
Inverse protein folding is a fundamental task in computational protein design, which aims to design protein sequences that fold into the desired backbone structures. While the deve…
TokenSelect: Efficient Long-Context Inference and Length Extrapolation for LLMs via Dynamic Token-Level KV Cache Selection
Wei Wu, Zhuoshi Pan, Chao Wang +6
Rapid advances in Large Language Models (LLMs) have spurred demand for processing extended context sequences in contemporary applications. However, this progress faces two challeng…
Structure-Enhanced Protein Instruction Tuning: Towards General-Purpose Protein Understanding with LLMs
Wei Wu, Chao Wang, Liyi Chen +6
Proteins, as essential biomolecules, play a central role in biological processes, including metabolic reactions and DNA replication. Accurate prediction of their properties and fun…