Difference between revisions of "Science Agents"

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* 2024-10: [https://arxiv.org/abs/2410.12771 Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models] ([https://github.com/FAIR-Chem/fairchem code], [https://huggingface.co/datasets/fairchem/OMAT24 datasets], [https://huggingface.co/fairchem/OMAT24 checkpoints], [https://ai.meta.com/blog/fair-news-segment-anything-2-1-meta-spirit-lm-layer-skip-salsa-sona/ blogpost])
 
* 2024-10: [https://arxiv.org/abs/2410.12771 Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models] ([https://github.com/FAIR-Chem/fairchem code], [https://huggingface.co/datasets/fairchem/OMAT24 datasets], [https://huggingface.co/fairchem/OMAT24 checkpoints], [https://ai.meta.com/blog/fair-news-segment-anything-2-1-meta-spirit-lm-layer-skip-salsa-sona/ blogpost])
 
* 2025-01: [https://www.nature.com/articles/s41586-025-08628-5 A generative model for inorganic materials design]
 
* 2025-01: [https://www.nature.com/articles/s41586-025-08628-5 A generative model for inorganic materials design]
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* 2025-04: [https://arxiv.org/abs/2504.14110 System of Agentic AI for the Discovery of Metal-Organic Frameworks]
  
 
===Chemistry===
 
===Chemistry===
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==LLMs Optimized for Science==
 
==LLMs Optimized for Science==
 
* 2022-11: [https://arxiv.org/abs/2211.09085 Galactica: A Large Language Model for Science]
 
* 2022-11: [https://arxiv.org/abs/2211.09085 Galactica: A Large Language Model for Science]
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* 2025-02: [https://arxiv.org/abs/2502.13107 MatterChat: A Multi-Modal LLM for Material Science]
 
* 2025-03: [https://arxiv.org/abs/2503.17604 OmniScience: A Domain-Specialized LLM for Scientific Reasoning and Discovery]
 
* 2025-03: [https://arxiv.org/abs/2503.17604 OmniScience: A Domain-Specialized LLM for Scientific Reasoning and Discovery]
 
* 2025-03: Google [https://huggingface.co/collections/google/txgemma-release-67dd92e931c857d15e4d1e87 TxGemma] (2B, 9B, 27B): [https://developers.googleblog.com/en/introducing-txgemma-open-models-improving-therapeutics-development/ drug development]
 
* 2025-03: Google [https://huggingface.co/collections/google/txgemma-release-67dd92e931c857d15e4d1e87 TxGemma] (2B, 9B, 27B): [https://developers.googleblog.com/en/introducing-txgemma-open-models-improving-therapeutics-development/ drug development]

Latest revision as of 09:59, 10 May 2025

AI Use-cases for Science

Literature

LLM extract data from papers

AI finding links in literature

(Pre) Generate Articles

Explanation

Autonomous Ideation

Adapting LLMs to Science

AI/LLM Control of Scientific Instruments/Facilities

AI/ML Methods tailored to Science

Regression (Data Fitting)

Tabular Classification/Regression

Symbolic Regression

Literature Discovery

Commercial

Bio

AI/ML Methods in Science

Chemistry

Biology

Medicine

See: AI_Agents#Medicine

Successes

AI/ML Methods co-opted for Science

Mechanistic Interpretability

Train large model on science data. Then apply mechanistic interpretability (e.g. sparse autoencoders, SAE) to the feature/activation space.

Uncertainty

Science Benchmarks

Science Agents

Reviews

Specific

Science Multi-Agent Setups

AI Science Systems

Inorganic Materials Discovery

Chemistry

LLMs Optimized for Science

Impact of AI in Science

Related Tools

Literature Search

Data Visualization

Generative

Chemistry

Science Datasets

See Also

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