Revisiting the Uniform Information Density Hypothesis
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Abstract (arXiv)
The uniform information density (UID) hypothesis posits a preference among language users for utterances structured such that information is distributed uniformly across a signal. While its implications on language production have been well explored, the hypothesis potentially makes predictions about language comprehension and linguistic acceptability as well. Further, it is unclear how uniformity in a linguistic signal -- or lack thereof -- should be measured, and over which linguistic unit, e.g., the sentence or language level, this uniformity should hold. Here we investigate these facets of the UID hypothesis using reading time and acceptability data. While our reading time results are generally consistent with previous work, they are also consistent with a weakly super-linear effect of surprisal, which would be compatible with UID's predictions. For acceptability judgments, we find clearer evidence that non-uniformity in information density is predictive of lower acceptability. We then explore multiple operationalizations of UID, motivated by different interpretations of the original hypothesis, and analyze the scope over which the pressure towards uniformity is exerted. The explanatory power of a subset of the proposed operationalizations suggests that the strongest trend may be a regression towards a mean surprisal across the language, rather than the phrase, sentence, or document -- a finding that supports a typical interpretation of UID, namely that it is the byproduct of language users maximizing the use of a (hypothetical) communication channel.
Key facts. Cited by 63 papers in the map (data through 7 Oct 2026). Builds on 12 of its 60 references that are in the map. First posted on arXiv 23 Sep 2021.
Builds on
12 of 60 references.
References · 12
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2016Pointer Sentinel Mixture Modelscited by 2,992
- 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,898
- 2019Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contextcited by 1,830
- 2018Neural Network Acceptability Judgmentscited by 952
- 2020On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behaviorcited by 115
- 2020If beam search is the answer, what was the question?cited by 114
- 2020As Good as New. How to Successfully Recycle English GPT-2 to Make Models for Other Languagescited by 54
- 2021Lower Perplexity is Not Always Human-Likecited by 52
- 2017The Natural Stories Corpuscited by 40
- 2021A Cognitive Regularizer for Language Modelingcited by 11
- 2019Availability-Based Production Predicts Speakers' Real-time Choices of Mandarin Classifierscited by 2
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Citing papers per year: 2021: 1; 2022: 10; 2023: 15; 2024: 13; 2025: 11; 2026: 13.
63 papers.
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- 2022Truncation Sampling as Language Model Desmoothingcited by 121
- 2022Efficient Transformers with Dynamic Token Poolingcited by 75
- 2023Testing the Predictions of Surprisal Theory in 11 Languagescited by 75
- 2023GPT-who: An Information Density-based Machine-Generated Text Detectorcited by 38
- 2022A Measure-Theoretic Characterization of Tight Language Modelscited by 32
- 2025LLM Probability Concentration: How Alignment Shrinks the Generative Horizoncited by 26
- 2021A surprisal--duration trade-off across and within the world's languagescited by 22
- 2023Information Value: Measuring Utterance Predictability as Distance from Plausible Alternativescited by 22
- 2025Anything Goes? A Crosslinguistic Study of (Im)possible Language Learning in LMscited by 20
- 2022On the Effect of Anticipation on Reading Timescited by 18
- 2024On the Role of Context in Reading Time Predictioncited by 17
- 2023A Cross-Linguistic Pressure for Uniform Information Density in Word Ordercited by 16
38 more
- 2024Surprise! Uniform Information Density Isn't the Whole Story: Predicting Surprisal Contours in Long-form Discoursecited by 14
- 2024On the Proper Treatment of Tokenization in Psycholinguisticscited by 12
- 2022Estimating the Entropy of Linguistic Distributionscited by 11
- 2022Analyzing Wrap-Up Effects through an Information-Theoretic Lenscited by 10
- 2024What Goes Into a LM Acceptability Judgment? Rethinking the Impact of Frequency and Lengthcited by 10
- 2025Language Models Grow Less Humanlike beyond Phase Transitioncited by 10
- 2026The Roots of Performance Disparity in Multilingual Language Models: Intrinsic Modeling Difficulty or Design Choices?cited by 10
- 2024Towards a Similarity-adjusted Surprisal Theorycited by 9
- 2023Revisiting Entropy Rate Constancy in Textcited by 7
- 2025The Harmonic Structure of Information Contourscited by 7
- 2024Revenge of the Fallen? Recurrent Models Match Transformers at Predicting Human Language Comprehension Metricscited by 6
- 2025Measuring AI "Slop" in Textcited by 6
- 2023Revisiting the Optimality of Word Lengthscited by 5
- 2025The time scale of redundancy between prosody and linguistic contextcited by 4
- 2023How do decoding algorithms distribute information in dialogue responses?cited by 3
- 2023Quantifying the perceptual value of lexical and non-lexical channels in speechcited by 3
- 2026Is Information Density Uniform when Utterances are Grounded on Perception and Discourse?cited by 3
- 2022How Adults Understand What Young Children Saycited by 2
- 2022Discourse Context Predictability Effects in Hindi Word Ordercited by 2
- 2023On the Depth between Beam Search and Exhaustive Search for Text Generationcited by 2
- 2024When Stereotypes GTG: The Impact of Predictive Text Suggestions on Gender Bias in Human-AI Co-Writingcited by 2
- 2025Strategic resource allocation in memory encoding: An efficiency principle shaping language processingcited by 2
- 2025Investigating Gender Bias in LLM-Generated Stories via Psychological Stereotypescited by 2
- 2025Identifying the Periodicity of Information in Natural Languagecited by 2
- 2026On the Proper Treatment of Units in Surprisal Theorycited by 2
- 2022Sentence Ambiguity, Grammaticality and Complexity Probescited by 1
- 2023Utility-Probability Duality of Neural Networkscited by 1
- 2023Are words equally surprising in audio and audio-visual comprehension?cited by 1
- 2023Content Reduction, Surprisal and Information Density Estimation for Long Documentscited by 1
- 2023Measuring Information in Text Explanationscited by 1
- 2023UID as a Guiding Metric for Automated Authorship Obfuscationcited by 1
- 2023Predicting Human Translation Difficulty with Neural Machine Translationcited by 1
- 2024Language models emulate certain cognitive profiles: An investigation of how predictability measures interact with individual differencescited by 1
- 2024Reverse-Engineering the Readercited by 1
- 2025Eye Tracking Based Cognitive Evaluation of Automatic Readability Assessment Methodscited by 1
- 2026Surprisal and Metaphor Novelty Judgments: Moderate Correlations and Divergent Scaling Effects Revealed by Corpus-Based and Synthetic Datasetscited by 1
- 2026Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisalcited by 1
- 2026Measuring and Mitigating Post-hoc Rationalization in Reverse Chain-of-Thought Generationcited by 1
50 most cited of 63 All 63 (JSON)
- 2026Scoring Without the Engine: Validating a Deterministic, Manipulation-Resistant Content Score for Generative Engines, End to End7 Sep 2026
- 2026Syntactic Belief Update as the Driver of Garden Path Processing Difficulty25 Jun 2026
- 2026Surprisal Minimisation over Goal-directed Alternatives Predicts Production Choice in Dialogue1 May 2026
- 2026On the Proper Treatment of Units in Surprisal Theory30 Apr 2026
- 2026Diffusion-CAM: Faithful Visual Explanations for dMLLMs13 Apr 2026
- 2026Expect the Unexpected? Testing the Surprisal of Salient Entities12 Apr 2026
- 2026N-gram-like Language Models Predict Naturalistic Reading Time Best10 Mar 2026
- 2026Time Series, Vision, and Language: Exploring the Limits of Alignment in Contrastive Representation Spaces22 Feb 2026
- 2026Is Information Density Uniform when Utterances are Grounded on Perception and Discourse?16 Feb 2026
- 2026Measuring and Mitigating Post-hoc Rationalization in Reverse Chain-of-Thought Generation16 Feb 2026
- 2026Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal14 Jan 2026
- 2026The Roots of Performance Disparity in Multilingual Language Models: Intrinsic Modeling Difficulty or Design Choices?12 Jan 2026
38 more
- 2026Surprisal and Metaphor Novelty Judgments: Moderate Correlations and Divergent Scaling Effects Revealed by Corpus-Based and Synthetic Datasets5 Jan 2026
- 2025Identifying the Periodicity of Information in Natural Language31 Oct 2025
- 2025Revisiting the UID Hypothesis in LLM Reasoning Traces11 Oct 2025
- 2025Measuring AI "Slop" in Text23 Sep 2025
- 2025Investigating Gender Bias in LLM-Generated Stories via Psychological Stereotypes5 Aug 2025
- 2025LLM Probability Concentration: How Alignment Shrinks the Generative Horizon22 Jun 2025
- 2025The Harmonic Structure of Information Contours4 Jun 2025
- 2025Strategic resource allocation in memory encoding: An efficiency principle shaping language processing18 Mar 2025
- 2025The time scale of redundancy between prosody and linguistic context14 Mar 2025
- 2025Language Models Grow Less Humanlike beyond Phase Transition26 Feb 2025
- 2025Anything Goes? A Crosslinguistic Study of (Im)possible Language Learning in LMs26 Feb 2025
- 2025Eye Tracking Based Cognitive Evaluation of Automatic Readability Assessment Methods16 Feb 2025
- 2024Learning to Write Rationally: How Information Is Distributed in Non-Native Speakers' Essays5 Nov 2024
- 2024What Goes Into a LM Acceptability Judgment? Rethinking the Impact of Frequency and Length4 Nov 2024
- 2024Towards a Similarity-adjusted Surprisal Theory23 Oct 2024
- 2024Surprise! Uniform Information Density Isn't the Whole Story: Predicting Surprisal Contours in Long-form Discourse21 Oct 2024
- 2024Reverse-Engineering the Reader16 Oct 2024
- 2024On the Proper Treatment of Tokenization in Psycholinguistics3 Oct 2024
- 2024When Stereotypes GTG: The Impact of Predictive Text Suggestions on Gender Bias in Human-AI Co-Writing30 Sep 2024
- 2024Thesis proposal: Are We Losing Textual Diversity to Natural Language Processing?15 Sep 2024
- 2024On the Role of Context in Reading Time Prediction12 Sep 2024
- 2024Language models emulate certain cognitive profiles: An investigation of how predictability measures interact with individual differences7 Jun 2024
- 2024That's Optional: A Contemporary Exploration of "that" Omission in English Subordinate Clauses31 May 2024
- 2024Revenge of the Fallen? Recurrent Models Match Transformers at Predicting Human Language Comprehension Metrics30 Apr 2024
- 2024To Drop or Not to Drop? Predicting Argument Ellipsis Judgments: A Case Study in Japanese17 Apr 2024
- 2023Predicting Human Translation Difficulty with Neural Machine Translation19 Dec 2023
- 2023Revisiting the Optimality of Word Lengths6 Dec 2023
- 2023UID as a Guiding Metric for Automated Authorship Obfuscation5 Nov 2023
- 2023Information Value: Measuring Utterance Predictability as Distance from Plausible Alternatives20 Oct 2023
- 2023GPT-who: An Information Density-based Machine-Generated Text Detector9 Oct 2023
- 2023Measuring Information in Text Explanations6 Oct 2023
- 2023Content Reduction, Surprisal and Information Density Estimation for Long Documents12 Sep 2023
- 2023On the Depth between Beam Search and Exhaustive Search for Text Generation25 Aug 2023
- 2023Are words equally surprising in audio and audio-visual comprehension?14 Jul 2023
- 2023Testing the Predictions of Surprisal Theory in 11 Languages7 Jul 2023
- 2023Quantifying the perceptual value of lexical and non-lexical channels in speech7 Jul 2023
- 2023A Cross-Linguistic Pressure for Uniform Information Density in Word Order6 Jun 2023
- 2023Utility-Probability Duality of Neural Networks24 May 2023
50 newest of 63 All 63 (JSON)
- 2026Diffusion-CAM: Faithful Visual Explanations for dMLLMscited by 1
- 2026Diffusion-CAM: Faithful Visual Explanations for dMLLMs13 Apr 2026
- 2022Truncation Sampling as Language Model Desmoothingcited by 121
- 2022Efficient Transformers with Dynamic Token Poolingcited by 75
- 2023Testing the Predictions of Surprisal Theory in 11 Languagescited by 75
- 2023GPT-who: An Information Density-based Machine-Generated Text Detectorcited by 38
- 2022A Measure-Theoretic Characterization of Tight Language Modelscited by 32
- 2021A surprisal--duration trade-off across and within the world's languagescited by 22
- 2023Information Value: Measuring Utterance Predictability as Distance from Plausible Alternativescited by 22
- 2025Anything Goes? A Crosslinguistic Study of (Im)possible Language Learning in LMscited by 20
- 2022On the Effect of Anticipation on Reading Timescited by 18
- 2024On the Role of Context in Reading Time Predictioncited by 17
- 2023A Cross-Linguistic Pressure for Uniform Information Density in Word Ordercited by 16
- 2024Surprise! Uniform Information Density Isn't the Whole Story: Predicting Surprisal Contours in Long-form Discoursecited by 14
12 most cited of 57 All 57 (JSON)
- 2026Scoring Without the Engine: Validating a Deterministic, Manipulation-Resistant Content Score for Generative Engines, End to End7 Sep 2026
- 2026Syntactic Belief Update as the Driver of Garden Path Processing Difficulty25 Jun 2026
- 2026Surprisal Minimisation over Goal-directed Alternatives Predicts Production Choice in Dialogue1 May 2026
- 2026On the Proper Treatment of Units in Surprisal Theory30 Apr 2026
- 2026Expect the Unexpected? Testing the Surprisal of Salient Entities12 Apr 2026
- 2026N-gram-like Language Models Predict Naturalistic Reading Time Best10 Mar 2026
- 2026Time Series, Vision, and Language: Exploring the Limits of Alignment in Contrastive Representation Spaces22 Feb 2026
- 2026Is Information Density Uniform when Utterances are Grounded on Perception and Discourse?16 Feb 2026
- 2026Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal14 Jan 2026
- 2026The Roots of Performance Disparity in Multilingual Language Models: Intrinsic Modeling Difficulty or Design Choices?12 Jan 2026
- 2025Identifying the Periodicity of Information in Natural Language31 Oct 2025
- 2025Measuring AI "Slop" in Text23 Sep 2025
12 newest of 57 All 57 (JSON)