mlsanityData to 7 Oct 2026

Do Language Models Exhibit Human-like Structural Priming Effects?

arXiv 2406.04847 ↗First posted 7 Jun 2024cs.CLcited by 21

Not on the map. Why?

Abstract (arXiv)

We explore which linguistic factors -- at the sentence and token level -- play an important role in influencing language model predictions, and investigate whether these are reflective of results found in humans and human corpora (Gries and Kootstra, 2017). We make use of the structural priming paradigm, where recent exposure to a structure facilitates processing of the same structure. We don't only investigate whether, but also where priming effects occur, and what factors predict them. We show that these effects can be explained via the inverse frequency effect, known in human priming, where rarer elements within a prime increase priming effects, as well as lexical dependence between prime and target. Our results provide an important piece in the puzzle of understanding how properties within their context affect structural prediction in language models.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 23 of its 89 references that are in the map. First posted on arXiv 7 Jun 2024.

Builds on

23 of 89 references.

References · 23

  1. 2022Training language models to follow instructions with human feedbackcited by 15,712
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  3. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
  4. 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,413
  5. 2020MPNet: Masked and Permuted Pre-training for Language Understandingcited by 973
  6. 2023The Falcon Series of Open Language Modelscited by 526
  7. 2023Zephyr: Direct Distillation of LM Alignmentcited by 498
  8. 2019Neural Language Models as Psycholinguistic Subjects: Representations of Syntactic Statecited by 137
  9. 2020Syntactic Structure from Deep Learningcited by 99
  10. 2021Structural Persistence in Language Models: Priming as a Window into Abstract Language Representationscited by 44
  11. 2023Understanding In-Context Learning via Supportive Pretraining Datacited by 41
  12. 2022Characterizing Intrinsic Compositionality in Transformers with Tree Projectionscited by 40
11 more
  1. 2019Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Modelscited by 29
  2. 2020Investigating representations of verb bias in neural language modelscited by 22
  3. 2022Language model acceptability judgements are not always robust to contextcited by 22
  4. 2018A Neural Model of Adaptation in Readingcited by 18
  5. 2023Structural Priming Demonstrates Abstract Grammatical Representations in Multilingual Language Modelscited by 16
  6. 2023Transparency at the Source: Evaluating and Interpreting Language Models With Access to the True Distributioncited by 10
  7. 2023Feature Interactions Reveal Linguistic Structure in Language Modelscited by 8
  8. 2020diagNNose: A Library for Neural Activation Analysiscited by 7
  9. 2023Attribution and Alignment: Effects of Local Context Repetition on Utterance Production and Comprehension in Dialoguecited by 4
  10. 2024SPAWNing Structural Priming Predictions from a Cognitively Motivated Parsercited by 3
  11. 2024Modeling Bilingual Sentence Processing: Evaluating RNN and Transformer Architectures for Cross-Language Structural Primingcited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 11; 2026: 8.

21 papers.

Sort:

By area:

  1. 2025Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketchingcited by 116
  2. 2025Herd Behavior: Investigating Peer Influence in LLM-based Multi-Agent Systemscited by 15
  3. 2025On the Acquisition of Shared Grammatical Representations in Bilingual Language Modelscited by 7
  4. 2025Strong Memory, Weak Control: An Empirical Study of Executive Functioning in LLMscited by 6
  5. 2025Large Language Models as Psychological Simulators: A Methodological Guidecited by 6
  6. 2024Is In-Context Learning a Type of Error-Driven Learning? Evidence from the Inverse Frequency Effect in Structural Primingcited by 3
  7. 2025How LLMs Comprehend Temporal Meaning in Narratives: A Case Study in Cognitive Evaluation of LLMscited by 3
  8. 2025The Power of Stories: Narrative Priming Shapes How LLM Agents Collaborate and Competecited by 2
  9. 2025Social Simulations with Large Language Model Risk Utopian Illusioncited by 2
  10. 2025A Linguistically Motivated Analysis of Intonational Phrasing in Text-to-Speech Systems: Revealing Gaps in Syntactic Sensitivitycited by 1
  11. 2025semantic-features: A User-Friendly Tool for Studying Contextual Word Embeddings in Interpretable Semantic Spacescited by 1
  12. 2026In-Context Learning in Speech Language Models: Analyzing the Role of Acoustic Features, Linguistic Structure, and Induction Headscited by 1
9 more
  1. 2026Surprisal Minimisation over Goal-directed Alternatives Predicts Production Choice in Dialoguecited by 1
  2. 2026Food Noise & False Safety: A Systematic Evaluation of How LLMs Fail to Adapt to Eating Disorder Queries with Clinician Feedbackcited by 1
  3. 2024Animate, or Inanimate, That is the Question for Large Language Modelscited by 0
  4. 2025Towards Human Cognition: Visual Context Guides Syntactic Priming in Fusion-Encoded Modelscited by 0
  5. 2026Is Length Really A Liability? An Evaluation of Multi-turn LLM Conversations using BoolQcited by 0
  6. 2026The Effects of Visual Priming on Cooperative Behavior in Vision-Language Modelscited by 0
  7. 2026Analysis of the Neglect-Zero Effect in Large Language Modelscited by 0
  8. 2026Instruction-Tuned Models Locally Reuse Human Syntax More Than Humans Docited by 0
  9. 2026Patterns of Priming in Production: Lexical, Semantic and Structural Alignment in Language Model Generationcited by 0