AI RESEARCH
Latent Chain-of-Thought Improves Structured-Data Transformers
arXiv CS.LG
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ArXi:2605.11262v1 Announce Type: new Chain-of-thought and broadly test-time compute are known to augment the expressive capabilities of language models and have led to major innovations in reasoning. Motivated by this success, this paper explores latent chain-of-thought as well as the impact of depth and looping for time-series and tabular data.