When Context Misleads: Surprisal, Energy and Attention Entropy as Metrics of Coherence Illusions in LLMs
cs.CL, cs.AI
Submitted: 2026-06-19
Updated: 2026-09-11
Comments: Accepted to the BlackboxNLP Workshop at EMNLP 2026
License: http://creativecommons.org/licenses/by/4.0/
The gist: Psycholinguistics studies show that human readers fall for coherence illusions: an incoherent discourse can seem coherent simply because a distractor matches what comes next.
Terminology
Abstract
Psycholinguistics studies show that human readers fall for coherence illusions: an incoherent discourse can seem coherent simply because a distractor matches what comes next. We investigate whether Dutch language models (6 monolingual and 4 multilingual) show the same behavior on texts that link back to earlier context with words such as 'again' and 'too'. First, we find that surprisal at the critical word tracks human acceptability judgments and eye-tracking data. Models are more surprised by incoherent continuations, but a matching distractor in the prior context reduces this surprisal. Second, attention entropy identifies heads that behave differently under coherence vs. incoherence. We find that ablating these heads shows transfer effects across experiments, suggesting a shared mechanism. Third, we introduce energy from the associative-memory literature as a metric to quantify discourse coherence. Taken together, our results show that coherence illusions arise in Dutch LLMs, with entropy and energy exposing mechanisms that operate across settings.
Sources
- Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier
- NRGPT: An Energy-based Alternative for GPT
- The Llama 3 Herd of Models
- EuroLLM-9B: Technical Report
- Probing for Reading Times
- Language Resources for Dutch Large Language Modelling
- GEITje 7B Ultra: A Conversational Model for Dutch
- Diverging Transformer Predictions for Human Sentence Processing: A Comprehensive Analysis of Agreement Attraction Effects
- Qwen3 Technical Report
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