ICLR Paper: State Information Dictates LLM Agent Generalization
An ICLR paper reveals that LLM agent cross-domain generalization in RL depends more on state information richness and planning complexity than surface similarity. Injecting interference items during training can effectively improve generalization performance.
2026-07-27 ~ 2026-07-27 · 2 related posts
- ICLR Paper: Injecting Distractors Improves Cross-Domain Generalization in LLM Agents — zhaoran_wang · 2026-07-27
- RL study finds LLM agents generalize better with richer state information than realistic tasks — Graham_dePenros · 2026-07-27