arXiv Machine Learning June 2, 2026 By Lei Yang, Siyu Ding, Deyi Xiong

A Local Perturbation Theory for Cross-Domain Interference and Recovery in Multi-Domain RL

Read the original on arXiv Machine Learning →

arXiv:2606. 02398v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training improves large language models (LLMs) on individual domains such as mathematical reasoning, code generation, question answering, and creative writing (CW), but training on one domain often degrades performance on others.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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