Revisiting Entropy Rate Constancy in Text (2023.findings-emnlp)

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Challenge: Existing evidence supports the uniform information density hypothesis . however, we re-evaluate the hypothesis with neural language models .
Approach: They propose to use n-gram language models to argue that English documents exhibit entropy rate constancy . they re-evaluate the claims of Genzel and Charniak with neural language models .
Outcome: The proposed hypothesis fails to support the proposed hypothesis with language models.

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Revisiting the Uniform Information Density Hypothesis (2021.emnlp-main)

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Challenge: The uniform information density hypothesis posits a preference among language users for utterances structured such that information is distributed uniformly across a signal.
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Surprise! Uniform Information Density Isn’t the Whole Story: Predicting Surprisal Contours in Long-form Discourse (2024.emnlp-main)

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Challenge: Uniform Information Density (UID) hypothesis posits that speakers tend to distribute information evenly across linguistic units to achieve efficient communication.
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Revisiting the Uniform Information Density Hypothesis in LLM Reasoning (2026.findings-acl)

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Challenge: a recent study has highlighted the fragility of Chain-of-Thought reasoning . a hypothesis suggests that effective communication is achieved by maintaining a stable flow of information.
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A Cognitive Regularizer for Language Modeling (2021.acl-long)

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Challenge: a uniform information density hypothesis is used to explain certain linguistic phenomena . a regularizer that encodes the UID hypothesis can be used for language training .
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The Harmonic Structure of Information Contours (2025.acl-long)

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Challenge: Language typically does not maintain a uniform information rate, but it fluctuates around a global average . a new study suggests periodicity may be a factor in information rate oscillations .
Approach: They propose a hypothesis that language does not maintain a uniform information rate . they apply harmonic regression and introduce a new extension to detect periodicity .
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Is Information Density Uniform when Utterances are Grounded on Perception and Discourse? (2026.eacl-long)

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Challenge: Existing studies on the distribution of information in visually grounded contexts have focused on text-only inputs.
Approach: They propose to use multilingual vision-and-language models to estimate surprisal . they find grounding on perception increases uniformity across typologically diverse languages .
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That’s Optional: A Contemporary Exploration of “that” Omission in English Subordinate Clauses (2024.acl-short)

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Challenge: Uniform information density (UID) hypothesis posits speakers optimize the communicative properties of their utterances by avoiding spikes in information.
Approach: They propose to extend the information-uniformity principles by the notion of entropy to estimate the UID manifestations in the usecase of syntactic reduction choices.
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How do decoding algorithms distribute information in dialogue responses? (2023.findings-eacl)

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Challenge: Using different decoding algorithms, we find that human dialogue generation is beneficial for adherence to the Uniform Information Density principle.
Approach: They investigate whether decoding algorithms implicitly follow the Uniform Information Density principle by distributing information evenly in utterances.
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A Cross-Linguistic Pressure for Uniform Information Density in Word Order (2023.tacl-1)

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Challenge: a recent study has compared real and counterfactual word orders, but one functional pressure has been overlooked . a study of 10 typologically diverse languages shows that real word orders have greater uniformity than reverse word orders .
Approach: They propose to test whether a pressure for UID may have influenced word order patterns cross-linguistically.
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Uniform Information Density and Syntactic Reduction: Revisiting *that*-Mentioning in English Complement Clauses (2025.emnlp-main)

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Challenge: Uniform Information Density (UID) hypothesis suggests that speakers exploit this variability to maintain a consistent rate of information transmission during language production.
Approach: They propose that speakers exploit this variability to maintain a consistent rate of information transmission during language production.
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