Nanqing Dong

Knowledge-to-Verification: Unlocking Reinforcement Learning with Verifiable Rewards for LLMs in Knowledge-Intensive Domains

Rethinking Multi-Omics LLMs from the Perspective of Omics-Encoding

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

Bidirectional Representations Augmented Autoregressive Biological Sequence Generation: Application in De Novo Peptide Sequencing

COMET: Benchmark for Comprehensive Biological Multi-omics Evaluation Tasks and Language Models

Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing

RankNovo: A Universal Reranking Approach for Robust De Novo Peptide Sequencing

Distilling Non-Autoregressive Model Knowledge for Autoregressive De Novo Peptide Sequencing

Two Heads Are Better Than One: A Multi-Agent System Has the Potential to Improve Scientific Idea Generation