collaborators

7 papers

cs.LG2026

ResearchClawBench: A Benchmark for End-to-End Autonomous Scientific Research

Wanghan Xu, Shuo Li, Tianlin Ye +48

AI coding agents are increasingly used for scientific work, but their end-to-end autonomous research capability remains difficult to verify. We present ResearchClawBench, a benchma…

q-bio.QM2025

Accurate de novo sequencing of the modified proteome with OmniNovo

Yuhan Chen, Shang Qu, Zhiqiang Gao +13

Post-translational modifications (PTMs) serve as a dynamic chemical language regulating protein function, yet current proteomic methods remain blind to a vast portion of the modifi…

cs.LG2025

Bidirectional Representations Augmented Autoregressive Biological Sequence Generation

Xiang Zhang, Jiaqi Wei, Zijie Qiu +5

Autoregressive (AR) models, common in sequence generation, are limited in many biological tasks such as de novo peptide sequencing and protein modeling by their unidirectional natu…

cs.CL2025

Unifying Tree Search Algorithm and Reward Design for LLM Reasoning: A Survey

Jiaqi Wei, Xiang Zhang, Yuejin Yang +10

Deliberative tree search is a cornerstone of modern Large Language Model (LLM) research, driving the pivot from brute-force scaling toward algorithmic efficiency. This single parad…

q-bio.BM2025

Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing

Xiang Zhang, Jiaqi Wei, Zijie Qiu +4

Peptide sequencing-the process of identifying amino acid sequences from mass spectrometry data-is a fundamental task in proteomics. Non-Autoregressive Transformers (NATs) have prov…

cs.LG2025

Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing

Zijie Qiu, Jiaqi Wei, Xiang Zhang +6

De novo peptide sequencing is a critical task in proteomics. However, the performance of current deep learning-based methods is limited by the inherent complexity of mass spectrome…