Large Language Model– tag –
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OSTI.GOV: AI and Autonomous Labs Revolutionize Metal-Organic Framework (MOF) Discovery, Streamlining Synthesis to Evaluation
OSTI.GOV USA Overview This perspective highlights AI's role in revolutionizing Metal-Organic Framework (MOF) discovery by integrating AI with automated high-throughput (HT) technologies. It discusses how autonomous labs, combined with La... -
NVIDIA and Key Japanese Partners Leverage Nemotron to Accelerate Localized AI Models and Materials R&D Agent AI Workflows
Quiver Quantitative Japan Overview NVIDIA announced that Japanese companies and research institutions, including ENEOS Holdings and Tokyo University of Science, are developing localized AI applications using NVIDIA Nemotron open models. ... -
Machine Learning Transforms Materials Science: From Property Prediction to Structural Design, Emphasizing LLM Validation
Academic Review / Journal Global Overview A new academic review highlights the transformative role of machine learning (ML) in materials science, detailing its impact on property prediction, novel material discovery, and process optimiza... -
arXiv Paper: Model-Agnostic Graph Prompt Learning Significantly Enhances GNN Crystal Property Prediction Accuracy
arXiv International Overview This paper proposes a novel model-agnostic soft prompt learning framework to improve the crystal property prediction performance of Graph Neural Networks (GNNs). By incorporating node-level and graph-level so... -
ACS Publications Reviews LLM-Based Autonomous Agents in Heterogeneous Catalysis, Addressing Tool Integration and Outlook
ACS Publications USA Overview A review paper in ACS Publications systematically analyzes the current state and prospects of Large Language Model (LLM)-based autonomous agent systems for heterogeneous catalysis research. The paper identif... -
arXiv Paper: Hypothesis Evolution Protocol (HEP) Establishes Auditable Scientific Discovery Capabilities for LLM Agents
arXiv International Overview A Hypothesis Evolution Protocol (HEP) has been proposed as a novel agent harness for Large Language Model (LLM)-based scientific discovery. This protocol enables explicit and auditable hypothesis generation, ... -
Comprehensive Review Details Machine Learning’s Role in Materials Science, From GNNs to LLMs for Data-Driven Discovery
Nature Computational Materials International Overview A new review paper offers a comprehensive analysis of machine learning's advancements in data-driven discovery and functional applications within materials science. Key technologies l... -
Nvidia-Backed AI Infrastructure Startup Fireworks Raises $1.51 Billion, Reaching $17.5 Billion Valuation with Over $1 Billion Annualized Revenue
WSAU USA Overview Nvidia-backed AI infrastructure startup Fireworks raised $1.51 billion in a Series D funding round, valuing the company at $17.5 billion. The funding will be used to expand its engineering team and global compute capaci... -
FDA Clears UpDoc’s LLM Diabetes App, Grants Breakthrough Status to Aidoc’s AI Radiology Tool
MarketScale USA Overview The U.S. FDA has granted De Novo clearance for UpDoc's patient-facing large language model application for diabetes management, which provides insulin dosing instructions based on physician-authored plans. Concur... -
LLM Coordinated Bench: New Multi-Agent Coordination Benchmark Launched, Gemini 3.1 Pro Matches Top MARL Agents in Long-Term Tasks
r/MachineLearning (Reddit) Unknown Overview A new study introduces the 'LLM Coordinated Bench' benchmark to evaluate LLM agents' coordination capabilities in long-term, open-ended environments. Assessing 13 contemporary LLMs, most agents...
