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Learning to Coach for Experiential Learning

Paper recorded by Signals 4 on 2026-09-14 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-14 on arXiv · recorded by Signals 4 on 2026-09-15

Category: cs.CL · 自然语言处理 · first seen 2026-09-15

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-Coach to extract actionable experiential knowledge from an actor model's previous trajectory. The actor remains frozen, while the LLM-as-a-Coach is trained to maximize a re

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#42 most recent of 186 cs.CL papers we have recorded · ↑ newer: Inoculation Midtraining with Learned Neologisms · ↓ older: EvoOntology: A Self-Evolving Ontology Layer for Data Agents
Cite this page: Learning to Coach for Experiential Learning: the #42 most recent of 186 cs.CL papers we have recorded (as of 2026-09-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/learning-to-coach-for-experiential-learning.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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