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Mahowald, Kyle

  1. Dissociating language and thought in large language models
    2023/01/16 by Kyle Mahowald, Anna A. Ivanova, Mahowald, Kyle +9 · 12 voices
    #cs.CL #cs.AI
  2. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
    2024/09/18 by Zayne Sprague, Fangcong Yin, Sprague, Zayne +18 · 6 voices · 60 citations
    Computer Science · #Computability, Logic, AI Algorithms #cs.AI #cs.CL #cs.LG
  3. Mission: Impossible Language Models
    2024/01/12 by Julie Kallini, Isabel Papadimitriou, Kallini, Julie +7 · 7 voices · 6 citations
    Computer Science · #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling #cs.AI #cs.CL #cs.LG
  4. How linguistics learned to stop worrying and love the language models
    2025/01/28 by Richard Futrell, Kyle Mahowald, Futrell, Richard +1 · 6 voices · 21 citations
    Arts and Humanities · #Linguistic Education and Pedagogy
  5. Language Models Fail to Introspect About Their Knowledge of Language
    2025/03/10 by Siyuan Song, Jennifer Hu, Song, Siyuan +3 · 5 voices · 13 citations
    Computer Science · #Natural Language Processing Techniques #cs.AI #cs.CL
  6. With Little Power Comes Great Responsibility
    2020/10/13 by Dallas Card, Card, Dallas, Peter Henderson +9 · 7 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Software Engineering Research #Topic Modeling
  7. Both Direct and Indirect Evidence Contribute to Dative Alternation Preferences in Language Models
    2025/03/26 by Qing Yao, Kanishka Misra, Yao, Qing +5 · 2 voices · 9 citations
    Computer Science · Neuroscience · Social Sciences · #Language and cultural evolution #Neurobiology of Language and Bilingualism #Topic Modeling #cs.CL
  8. Deep Subjecthood: Higher-Order Grammatical Features in Multilingual BERT
    2021/01/26 by Papadimitriou, Isabel, Chi, Ethan A., Futrell, Richard +1 · 3 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences
  9. Are Language Models More Like Libraries or Like Librarians? Bibliotechnism, the Novel Reference Problem, and the Attitudes of LLMs
    2024/01/10 by Harvey Lederman, Kyle Mahowald, Lederman, Harvey +1 · 3 voices · 2 citations
    Arts and Humanities · #Digital Humanities and Scholarship #cs.CL
  10. Language Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the Missing AANNs
    2024/03/28 by Kanishka Misra, Misra, Kanishka, Kyle Mahowald +1 · 5 citations
    Computer Science · #Topic Modeling #Natural Language Processing Techniques
  11. What do tokens know about their characters and how do they know it?
    2022/06/06 by Ayush Kaushal, Kaushal, Ayush, Kyle Mahowald +1 · 3 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
  12. A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Construction
    2023/01/29 by Mahowald, Kyle · 3 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences
  13. A Method for Studying Semantic Construal in Grammatical Constructions with Interpretable Contextual Embedding Spaces
    2023/05/29 by Chronis, Gabriella, Mahowald, Kyle, Erk, Katrin · 3 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences
  14. Privileged Self-Access Matters for Introspection in AI
    2025/08/20 by Siyuan Song, Harvey Lederman, Song, Siyuan +5 · 2 voices · 7 citations
    Computer Science · Social Sciences · #Online Learning and Analytics #Ethics and Social Impacts of AI #Explainable Artificial Intelligence (XAI)
  15. Causal Interventions Reveal Shared Structure Across English Filler-Gap Constructions
    2025/05/21 by Sasha Boguraev, Christopher Potts, Boguraev, Sasha +3 · 1 voice · 5 citations
    #cs.CL #cs.AI
  16. Why is Winoground Hard? Investigating Failures in Visuolinguistic Compositionality
    2022/11/01 by Diwan, Anuj, Berry, Layne, Choi, Eunsol +2 · 2 citations
    #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  17. When classifying grammatical role, BERT doesn't care about word order...\n except when it matters
    2022/03/11 by Isabel Papadimitriou, Papadimitriou, Isabel, Richard Futrell +3 · 2 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
  18. Linguistic Generalizations are not Rules: Impacts on Evaluation of LMs
    2025/02/18 by Leonie Weissweiler, Kyle Mahowald, Weissweiler, Leonie +4 · 1 voice · 3 citations
    Arts and Humanities · Computer Science · #linguistics and terminology studies #Natural Language Processing Techniques
  19. Decrypting Cryptic Crosswords: Semantically Complex Wordplay Puzzles as a Target for NLP
    2021/04/17 by Joshua Rozner, Christopher Potts, Rozner, Josh +3 · 1 citation
    Computer Science · #Topic Modeling #Natural Language Processing Techniques #Authorship Attribution and Profiling
  20. Constructions are Revealed in Word Distributions
    2025/03/08 by Joshua Rozner, Leonie Weissweiler, Rozner, Joshua +5 · 1 voice · 1 citation
    #cs.CL
  21. What Can String Probability Tell Us About Grammaticality?
    2025/10/17 by Jennifer Hu, Jennifer J. Hu, Ethan Wilcox +10 · 1 voice · 3 citations
    Computer Science · Neuroscience · Social Sciences · #Language and cultural evolution #Natural Language Processing Techniques #Neurobiology of Language and Bilingualism #cs.AI #cs.CL
  22. Elaborative Simplification as Implicit Questions Under Discussion
    2023/05/17 by Yating Wu, William Sheffield, Wu, Yating +5 · 1 voice · 1 citation
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #cs.CL
  23. Is It JUST Semantics? A Case Study of Discourse Particle Understanding in LLMs
    2025/06/05 by Sheffield, William, Misra, Kanishka, Pyatkin, Valentina +3 · 2 citations
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences
  24. Models Can and Should Embrace the Communicative Nature of Human-Generated Math
    2024/09/25 by Sasha Boguraev, Ben Lipkin, Benjamin Lipkin +6 · 2 voices
    Engineering · #Robotics and Automated Systems #cs.AI #cs.CL