Tag: Curriculum Learning
All the articles with the tag "Curriculum Learning".
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Can Large Reasoning Models Self-Train?
本文提出Self-Rewarded Training (SRT) 方法,通过模型自一致性驱动强化学习实现无监督数学推理能力提升,初期性能媲美有监督方法,但因奖励黑客问题导致长期训练性能崩溃,并探索了提前停止和课程学习等缓解策略。
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ZeroSearch: Incentivize the Search Capability of LLMs without Searching
ZEROSEARCH introduces a reinforcement learning framework that enhances LLMs' search capabilities by simulating search engines with fine-tuned LLMs, achieving performance comparable to or better than real search engines without API costs through a curriculum-based rollout strategy.
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SATURN: SAT-based Reinforcement Learning to Unleash Language Model Reasoning
SATURN提出一个基于SAT问题的强化学习框架,通过课程学习和可控难度的SAT任务显著提升大型语言模型在SAT、数学和编程任务上的推理能力。
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Learning Like Humans: Advancing LLM Reasoning Capabilities via Adaptive Difficulty Curriculum Learning and Expert-Guided Self-Reformulation
This paper introduces Adaptive Difficulty Curriculum Learning (ADCL) and Expert-Guided Self-Reformulation (EGSR) to enhance LLM reasoning by dynamically adjusting training curricula and guiding models to reformulate expert solutions, achieving significant performance improvements over standard RL baselines on mathematical reasoning benchmarks.