mlsanityData to 7 Oct 2026

Semantic Change Characterization with LLMs using Rhetorics

arXiv 2407.16624 ↗First posted 23 Jul 2024cs.CLcited by 4

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Abstract (arXiv)

Languages continually evolve in response to societal events, resulting in new terms and shifts in meanings. These changes have significant implications for computer applications, including automatic translation and chatbots, making it essential to characterize them accurately. The recent development of LLMs has notably advanced natural language understanding, particularly in sense inference and reasoning. In this paper, we investigate the potential of LLMs in characterizing three types of semantic change: dimension, relation, and orientation. We achieve this by combining LLMs' Chain-of-Thought with rhetorical devices and conducting an experimental assessment of our approach using newly created datasets. Our results highlight the effectiveness of LLMs in capturing and analyzing semantic changes, providing valuable insights to improve computational linguistic applications.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 20 of its 52 references that are in the map. First posted on arXiv 23 Jul 2024.

Builds on

20 of 52 references.

References · 20

  1. 2019Language Models as Knowledge Bases?cited by 1,922
  2. 2023The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"cited by 399
  3. 2018WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representationscited by 370
  4. 2022Emergent Analogical Reasoning in Large Language Modelscited by 239
  5. 2022Language models show human-like content effects on reasoning taskscited by 171
  6. 2022The Unreliability of Explanations in Few-shot Prompting for Textual Reasoningcited by 169
  7. 2023Orca 2: Teaching Small Language Models How to Reasoncited by 157
  8. 2020SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detectioncited by 105
  9. 2022Testing the Ability of Language Models to Interpret Figurative Languagecited by 67
  10. 2018Survey of Computational Approaches to Lexical Semantic Changecited by 60
  11. 2021MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theoriescited by 46
  12. 2023Exploring the Potential of Large Language Models in Computational Argumentationcited by 42
8 more
  1. 2023Interpretable Word Sense Representations via Definition Generation: The Case of Semantic Change Analysiscited by 19
  2. 2021Challenges for Computational Lexical Semantic Changecited by 15
  3. 2023The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Changecited by 7
  4. 2024Analyzing Semantic Change through Lexical Replacementscited by 7
  5. 2024Using Synchronic Definitions and Semantic Relations to Classify Semantic Change Typescited by 7
  6. 2022Metaphorical Polysemy Detection: Conventional Metaphor meets Word Sense Disambiguationcited by 6
  7. 2024Survey in Characterizing Semantic Changecited by 5
  8. 2023Large Language Models on Lexical Semantic Change Detection: An Evaluationcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 1.

4 papers.

  1. 2024Bias in Large Language Models: Origin, Evaluation, and Mitigationcited by 77
  2. 2025Simulating a Bias Mitigation Scenario in Large Language Modelscited by 4
  3. 2025LSC-Eval: A General Framework to Evaluate Methods for Assessing Dimensions of Lexical Semantic Change Using LLM-Generated Synthetic Datacited by 1
  4. 2026Relation Geometry in Semantic Space of Language Modelscited by 0

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  1. 2026When Lexical Change Misleads: Rethinking Dynamic Topic Model Evaluation with Traditional and LLM-Based Metrics
  2. 2024MARS: Benchmarking the Metaphysical Reasoning Abilities of Language Models with a Multi-task Evaluation Dataset
  3. 2026Toward Responsible and Epistemically Grounded Multilingual LLMs for Computational Social Science and Humanities
  4. 2024EvoWiki: Evaluating LLMs on Evolving Knowledge
  5. 2024Unveiling LLMs: The Evolution of Latent Representations in a Dynamic Knowledge Graph
  6. 2025A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers
  7. 2025BeDiscovER: The Benchmark of Discourse Understanding in the Era of Reasoning Language Models
  8. 2025How LLMs Comprehend Temporal Meaning in Narratives: A Case Study in Cognitive Evaluation of LLMs