LLMs still fail at temporal reasoning, and a hierarchical HMM is proposed for extreme long contexts
beffjezos · x · 2026-07-27
A post argues that whoever figures out a temporal hierarchical hidden Markov model for LLMs over extreme long contexts will “print,” in response to a complaint that frontier models still fail at temporal reasoning: they produce giant essays, misunderstand time, and show a strong recency bias.
- The core criticism is that current frontier models remain weak at time-aware reasoning and conversation over very long contexts.
- The suggested direction is a temporal hierarchical HMM style approach for better long-context structure and memory.
- The post frames this as a potentially valuable breakthrough area rather than a solved capability.
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