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AI for Science开始“动手”了：机器人正式走进国家级实验室
当AI从算数据走向动手做实验，机器人已在国家级实验室里连续运行，科学发现迎来“实验室3.0”时代。
源络科技，推动AI for Science走进实验室3.0
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Agent-MD: Selective LLM Intervention with Event-Driven Escalation for Stateful GCMC--MD Campaigns
用LLM智能干预分子模拟，事件驱动升级机制让GCMC-MD计算更高效。
arXiv:2608.07637v1 Announce Type: new Abstract: Long-running molecular simulation campaigns require repeated continuation from saved states, provenanc…
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Leveraging Biokinetic Knowledge Priors for Data-Scarce Bioprocess Modeling
用生物动力学知识先验解决数据稀缺难题，为生物过程建模开辟新路径——ICML 2026 AI for Science 论文
arXiv:2607.20539v1 Announce Type: cross Abstract: While deep learning has accelerated drug discovery, its impact on biomanufacturing has been consider…
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AI for Auto-Research: Roadmap & User Guide
arXiv最新论文，系统梳理AI赋能自动科研的路线图与实操指南，涵盖从工具到方法的完整框架。
arXiv:2605.18661v2 Announce Type: replace Abstract: AI-assisted research is crossing a threshold: fully automated systems can now generate research pa…
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Bifidelity Parameter Estimation Using Conditional Diffusion Models
基于条件扩散模型的双保真参数估计新方法，融合高低保真数据提升推断精度与效率。
arXiv:2504.01894v2 Announce Type: replace Abstract: We present a bifidelity method for uncertainty quantification of parameter estimates in complex sy…
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From Experiments to Expertise: Scientific Knowledge Consolidation for AI-Driven Computational Physics
AI与物理交叉前沿，看如何将实验知识系统整合进计算物理模型，ICML研讨会力作。
arXiv:2603.13191v2 Announce Type: replace-cross Abstract: While large language models (LLMs) have transformed AI agents into proficient executors of c…
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LLM-Guided Test-Time Discovery of Quantum-Chemical Approximation Algorithms
LLM在测试时引导量子化学近似算法发现，开创AI for Science新范式
arXiv:2606.20729v1 Announce Type: cross Abstract: Quantum chemistry simulations underpin modern materials discovery, yet their impact is limited by st…
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SupraBench: A Benchmark for Supramolecular Chemistry
首个超分子化学AI基准测试，推动分子计算与新药研发
arXiv:2606.13477v1 Announce Type: cross Abstract: Supramolecular chemistry, which includes the study of non-covalent host-guest assemblies, has advanc…
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RetroReasoner: A Reasoning LLM for Strategic Retrosynthesis Prediction
用推理大模型破解化学逆合成难题，RetroReasoner教你如何策略性预测分子合成路线。
arXiv:2603.12666v2 Announce Type: replace Abstract: Retrosynthesis prediction aims to identify reactants that can synthesize a given product molecule.…
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Discovering heuristics in a complex SAT solver with large language models
大语言模型不再只是聊天，还能帮助复杂SAT求解器自动发掘高效启发式策略，开启AI辅助算法设计新范式。
arXiv:2507.22876v2 Announce Type: replace Abstract: The Satisfiability problem (SAT) is fundamental in computational complexity theory and has a wide …
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智源&清华合作成果登上Science：脑科学多模态基础模型Brainμ支撑揭示“记忆-睡眠”调控的神经机制
脑科学多模态基础模型Brainμ登上《Science》，首次揭示记忆通过重激活反向调控睡眠动态的神经机制，AI for Science再下一城。
研究表明，睡眠中的记忆重激活参与调控睡眠动态，为理解“记忆-睡眠”双向作用机制提供了新的实验证据。
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Uncovering Insights of Compound Flooding with Data-Driven AI
被KDD 2026收录的AI for Science研究，数据驱动AI揭示复合洪水形成机制
arXiv:2506.04281v2 Announce Type: replace Abstract: Compound flooding, driven by nonlinear interactions between multiple hydrometeorological factors, …
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Uncertainty-Calibrated Diffusion for Reliable 3D Molecular Graph Generation
新方法通过不确定性校准提升3D分子图生成的可靠性，有望推动药物发现与材料设计。
arXiv:2606.01595v1 Announce Type: new Abstract: Bayesian inference provides a principled framework for modeling epistemic uncertainty in neural networ…
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ClimAgent: LLM as Agents for Autonomous Open-ended Climate Science Analysis
LLM化身自主气候科学家，ClimAgent实现开放式的端到端科学分析，AI for Science新进展！
arXiv:2604.16922v3 Announce Type: replace Abstract: Climate research is pivotal for mitigating global environmental crises, yet the accelerating volum…
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Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review
首篇系统性综述，梳理大规模AI基础模型在神经科学中的模型、数据集与应用，跨学科桥接的必读参考。
arXiv:2510.16658v3 Announce Type: replace Abstract: The development of large-scale artificial intelligence (AI) models is influencing neuroscience res…
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Experiments in Agentic AI for Science
探索智能体AI在科学研究中的实验方法与前沿应用，揭示AI驱动科学发现的新路径。
arXiv:2605.26305v1 Announce Type: new Abstract: This paper details two novel frameworks for developing autonomous, agentic AI in scientific workflows.…
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LLM-driven design of physics-constrained constitutive models: two agents are better than one
双AI代理协同设计物理约束本构模型，比单模型更高效准确，揭示LLM在科学计算中的新范式。
arXiv:2605.23754v1 Announce Type: new Abstract: Developing constitutive models that capture how materials deform under load traditionally requires yea…
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Structure-Aware Masking for Protein Representation Learning
突破性结构感知掩码方法，提升蛋白质表征学习效能，为AI制药与蛋白质设计提供新思路
arXiv:2605.16581v1 Announce Type: new Abstract: Masked language modeling (MLM) is the standard objective for training protein language models, typical…