8 citations · 20 across the 19 of their papers we have counts for
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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…
Intern-S1: A Scientific Multimodal Foundation Model
Lei Bai, Zhongrui Cai, Yuhang Cao +173
In recent years, a plethora of open-source foundation models have emerged, achieving remarkable progress in some widely attended fields, with performance being quite close to that…
From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery
Jiaqi Wei, Yuejin Yang, Xiang Zhang +24
Artificial intelligence (AI) is reshaping scientific discovery, evolving from specialized computational tools into autonomous research partners. We position Agentic Science as a pi…
Dynamic Knowledge Exchange and Dual-diversity Review: Concisely Unleashing the Potential of a Multi-Agent Research Team
Weilun Yu, Shixiang Tang, Yonggui Huang +7
Scientific progress increasingly relies on effective collaboration among researchers, a dynamic that large language models (LLMs) have only begun to emulate. While recent LLM-based…
PRING: Rethinking Protein-Protein Interaction Prediction from Pairs to Graphs
Xinzhe Zheng, Hao Du, Fanding Xu +9
Deep learning-based computational methods have achieved promising results in predicting protein-protein interactions (PPIs). However, existing benchmarks predominantly focus on iso…
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…
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…
AI-Driven Automation Can Become the Foundation of Next-Era Science of Science Research
Renqi Chen, Haoyang Su, Shixiang Tang +7
The Science of Science (SoS) explores the mechanisms underlying scientific discovery, and offers valuable insights for enhancing scientific efficiency and fostering innovation. Tra…
Towards Efficient and Intelligent Laser Weeding: Method and Dataset for Weed Stem Detection
Dingning Liu, Jinzhe Li, Haoyang Su +5
Weed control is a critical challenge in modern agriculture, as weeds compete with crops for essential nutrient resources, significantly reducing crop yield and quality. Traditional…