arXiv Machine Learning June 29, 2026 By Xiang Gao, Kaiwen Dong, Yuguang Yao, Padmaja Jonnalagedda, Kamalika Das

Textual Belief States for World Models: Identifiable Representation Learning Under Strict Mediation

Read the original on arXiv Machine Learning →

arXiv:2606. 27681v1 Announce Type: new Abstract: World models in partially observed environments rely on latent representations that summarize interaction history, but in many modern LLM-based architectures predictive performance fails to reflect representation quality due to history bypass, rendering the latent state unidentifiable.

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