IR-Agent is a multi-agent LLM framework that emulates expert IR spectral analysis procedures to improve molecular structure elucidation accuracy and adaptability.
Biodiscoveryagent: An ai agent for designing genetic perturbation experiments
4 Pith papers cite this work. Polarity classification is still indexing.
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A principled reward design for tool selection and application in RL-trained LLMs delivers 17% gains over base models and 15% over SFT across benchmarks.
A review paper that surveys AI uses across the food innovation pipeline for sustainable proteins and identifies four strategic priorities for the emerging field.
A survey that deconstructs LLM agent systems via a methodology-centered taxonomy linking design principles to emergent behaviors, applications, and challenges.
citing papers explorer
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IR-Agent: Expert-Inspired LLM Agents for Structure Elucidation from Infrared Spectra
IR-Agent is a multi-agent LLM framework that emulates expert IR spectral analysis procedures to improve molecular structure elucidation accuracy and adaptability.
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ToolRL: Reward is All Tool Learning Needs
A principled reward design for tool selection and application in RL-trained LLMs delivers 17% gains over base models and 15% over SFT across benchmarks.
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Artificial Intelligence for Food Innovation
A review paper that surveys AI uses across the food innovation pipeline for sustainable proteins and identifies four strategic priorities for the emerging field.
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Large Language Model Agent: A Survey on Methodology, Applications and Challenges
A survey that deconstructs LLM agent systems via a methodology-centered taxonomy linking design principles to emergent behaviors, applications, and challenges.