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New 'Learning to Coach' framework enhances LLM experiential learning

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework called Learning to Coach (L2C) designed to improve how language models learn from experience. L2C trains a specialized LLM-as-a-Coach to distill actionable insights from an actor model's past performance, rather than relying on raw, lengthy trajectories. This coaching model is trained to enhance subsequent responses, both on the same problem and on new instances, by maximizing a reward based on the actor's guided output. Experiments in mathematical reasoning and text-based games show L2C surpasses standard self-refinement techniques and untrained coaching models, demonstrating effective knowledge transfer to different tasks and actors. AI

IMPACT This framework could lead to more efficient and effective training of AI models by extracting more valuable knowledge from their experiences.

RANK_REASON The cluster contains a research paper detailing a new framework for LLM training. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New 'Learning to Coach' framework enhances LLM experiential learning

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The cluster contains a research paper detailing a new framework for LLM training. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Guanheng Chen, Tianzhu Ye, Li Dong, Xun Wu, Shaohan Huang, Furu Wei ·

    Learning to Coach for Experiential Learning

    arXiv:2609.15851v1 Announce Type: new Abstract: Language models can learn from experience, but raw solution trajectories are often too long and noisy to provide effective guidance. In this work, we propose Learning to Coach (L2C), a framework that trains a dedicated LLM-as-a-Coac…

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