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New MMAI Gym trains Liquid Foundation Models for drug discovery

Researchers have developed the MMAI Gym for Science, a new platform designed to train foundation models specifically for drug discovery tasks. This gym provides curated molecular data, task-specific reasoning, and benchmarking tools. Using this gym, they trained an efficient Liquid Foundation Model (LFM) that demonstrates superior performance and efficiency compared to larger, general-purpose models on various molecular benchmarks, including molecular optimization and ADMET property prediction. AI

IMPACT This research could accelerate drug discovery by providing more efficient and effective AI models for molecular analysis and prediction.

RANK_REASON The cluster contains a research paper detailing a new methodology and model for scientific applications. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New MMAI Gym trains Liquid Foundation Models for drug discovery

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The cluster contains a research paper detailing a new methodology and model for scientific applications. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Maksim Kuznetsov, Zulfat Miftahutdinov, Rim Shayakhmetov, Mikolaj Mizera, Roman Schutski, Bogdan Zagribelnyy, Ivan Ilin, Nikita Bondarev, Thomas MacDougall, Mathieu Reymond, Mihir Bafna, Kaeli Kaymak-Loveless, Eugene Babin, Maxim Malkov, Mathias Lechner,… ·

    MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery

    arXiv:2603.03517v2 Announce Type: replace-cross Abstract: General-purpose large language models (LLMs) that rely on in-context learning do not reliably deliver the scientific understanding and performance required for drug discovery tasks. Simply increasing model size or introduc…