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Paper · arXiv

Coherence-Aware Distributional Evaluation of Open-Ended Text Generation

Existing open-ended generation metrics measure likelihood, lexical diversity, or distributional similarity in generic representation space, yet can miss fundamental dimensions of quality. A prominent blind spot is global coherence: a generated passage may be locally fluent while remaining globally contradictory, causally inconsistent, or topically disconnected. We identify representation as a central bottleneck in detecting these failures and introduce CHORD (Coherence-aware Hidden-state Open-generation Reference Distance), a coherence-sensitive distributional metric. CHORD encodes generated and human-written corpora in the hidden-state space of a frozen LLM using a coherence-eliciting pr...

AuthorsJinnuo Liu, Junhao Zhu, Weifeng Jiang et al.
Primary categorycs.CL
Published28 September 2026
Last updated at source29 September 2026
cs.CLcs.AI
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