Cover Image

Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhou, Lianhao, Ling, Hongyi, Fu, Cong, Huang, Yepeng, Sun, Michael, Yu, Wendi, Wang, Xiaoxuan, Li, Xiner, Su, Xingyu, Zhang, Junkai, Chen, Xiusi, Liang, Chenxing, Qian, Xiaofeng, Ji, Heng, Wang, Wei, Zitnik, Marinka, Ji, Shuiwang
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists
by: Zhou, Lianhao, et al.
Published: (2025)

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation
by: Yan, Keqiang, et al.
Published: (2025)

AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation
by: Gao, Shanghua, et al.
Published: (2026)

A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery
by: Zhang, Yu, et al.
Published: (2024)

Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models
by: Fu, Cong, et al.
Published: (2024)

Active Test-Time Adaptation: Theoretical Analyses and An Algorithm
by: Gui, Shurui, et al.
Published: (2024)

Discovering Physics Laws of Dynamical Systems via Invariant Function Learning
by: Gui, Shurui, et al.
Published: (2025)

Scaling Laws in Scientific Discovery with AI and Robot Scientists
by: Zhang, Pengsong, et al.
Published: (2025)

A Hierarchical Language Model For Interpretable Graph Reasoning
by: Khurana, Sambhav, et al.
Published: (2024)

Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization
by: Li, Xiner, et al.
Published: (2023)

Language Models for Controllable DNA Sequence Design
by: Su, Xingyu, et al.
Published: (2025)

Multimodal Medical Code Tokenizer
by: Su, Xiaorui, et al.
Published: (2025)

Prompting Decision Transformers for Zero-Shot Reach-Avoid Policies
by: Li, Kevin, et al.
Published: (2025)

Ken Utilization Layer: Hebbian Replay Within a Student's Ken for Adaptive Exercise Recommendation
by: Kuling, Grey, et al.
Published: (2025)

Geometry Informed Tokenization of Molecules for Language Model Generation
by: Li, Xiner, et al.
Published: (2024)

Empowering Biomedical Discovery with AI Agents
by: Gao, Shanghua, et al.
Published: (2024)

Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery
by: Bisht, Harshit, et al.
Published: (2026)

Complete and Efficient Graph Transformers for Crystal Material Property Prediction
by: Yan, Keqiang, et al.
Published: (2024)

Generalized Protein Pocket Generation with Prior-Informed Flow Matching
by: Zhang, Zaixi, et al.
Published: (2024)

Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design
by: Uehara, Masatoshi, et al.
Published: (2025)

Dynamic Search for Inference-Time Alignment in Diffusion Models
by: Li, Xiner, et al.
Published: (2025)

Complex LLM Planning via Automated Heuristics Discovery
by: Ling, Hongyi, et al.
Published: (2025)

Eliminating Position Bias of Language Models: A Mechanistic Approach
by: Wang, Ziqi, et al.
Published: (2024)

CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation
by: Jansen, Peter, et al.
Published: (2025)

FoldMark: Protecting Protein Generative Models with Watermarking
by: Zhang, Zaixi, et al.
Published: (2024)

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
by: Lu, Chris, et al.
Published: (2024)

PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models
by: Velez-Arce, Alejandro, et al.
Published: (2025)

Graph Representation Learning in Biomedicine
by: Li, Michelle M., et al.
Published: (2021)

Learning to Discover Regulatory Elements for Gene Expression Prediction
by: Su, Xingyu, et al.
Published: (2025)

Kosmos: An AI Scientist for Autonomous Discovery
by: Mitchener, Ludovico, et al.
Published: (2025)

Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning
by: Parashar, Shubham, et al.
Published: (2025)

Controllable Sequence Editing for Biological and Clinical Trajectories
by: Li, Michelle M., et al.
Published: (2025)

Mitigating Spurious Correlations in LLMs via Causality-Aware Post-Training
by: Gui, Shurui, et al.
Published: (2025)

Learning Generalized Medical Image Representations through Image-Graph Contrastive Pretraining
by: Khanna, Sameer, et al.
Published: (2024)

Greater than the Sum of Its Parts: Building Substructure into Protein Encoding Models
by: Calef, Robert, et al.
Published: (2025)

Repurposing Foundation Model for Generalizable Medical Time Series Classification
by: Huang, Nan, et al.
Published: (2024)

Beyond Sample-Level Feedback: Using Reference-Level Feedback to Guide Data Synthesis
by: Mehri, Shuhaib, et al.
Published: (2025)

DecisionFlow: Advancing Large Language Model as Principled Decision Maker
by: Chen, Xiusi, et al.
Published: (2025)

SR-Scientist: Scientific Equation Discovery With Agentic AI
by: Xia, Shijie, et al.
Published: (2025)

A Generative AI System for Biomedical Data Discovery with Grammar-Based Visualizations
by: Lange, Devin, et al.
Published: (2025)