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Incentivizing Self-Learning in Large Language Models via Reinforcement Learning

Paper recorded by Signals 4 on 2026-10-29 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.CL · 自然语言处理 · first seen 2026-10-30

Abstract

Large language models (LLMs) draw on parametric knowledge and retrieval-augmented generation (RAG) to solve knowledge-intensive tasks. Yet problem solving in unfamiliar domains calls for tightly coupled knowledge acquisition and reasoning, beyond factual retrieval and aggregation or learning solely from a preassembled context. We study self-learning -- autonomously retrieving, studying, and applyi

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#78 most recent of 628 cs.CL papers we have recorded · ↑ newer: Event-SAMA: Language-Grounded Video Object Segmentation on Neuromorphi · ↓ older: Evaluating Cultural Knowledge Editing in Vision-Language Models
Cite this page: Incentivizing Self-Learning in Large Language Models via Reinforcement Learning: the #78 most recent of 628 cs.CL papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/incentivizing-self-learning-in-large-language-models-via-reinforcement-learning.html
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