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Matching papers

Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning

28 upvotes · 22 JUL 2026 · Jian Hu, Huiying Li, Hao Zhang et al.

This paper introduces Molt, a lightweight PyTorch framework for agentic reinforcement learning that aims to simplify the development process by reducing the overhead of algorithm modifications and framework changes. Practitioners might care about Molt because it can help them build and train reinforcement learning models more efficiently.

reinforcement learningagentic reinforcement learningPyTorchscalable frameworksdistributed training

SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution

18 upvotes · 29 JUL 2026 · Zhiyuan Yao, Yuxin Chen, Zhengxi Lu et al.

This paper introduces SkillRise, a framework that enables large language model agents to learn skills across related tasks, allowing them to reuse solution patterns and improve performance on multiple tasks. Practitioners can use SkillRise to train more efficient LLM agents that can adapt to new tasks and improve their performance over time.

agentic reinforcement learningskill learningcontinual learningcross-task transferlanguage model agents