mlsanityData to 7 Oct 2026

Generative linguistics contribution to artificial intelligence: Where this contribution lies?

arXiv 2410.20221 ↗First posted 26 Oct 2024cs.CLcited by 7

Not on the map. Why?

Abstract (arXiv)

This article aims to characterize Generative linguistics (GL) contribution to artificial intelligence (AI), alluding to the debate among linguists and AI scientists on whether linguistics belongs to humanities or science. In this article, I will try not to be biased as a linguist, studying the phenomenon from an independent scientific perspective. The article walks the researcher/reader through the scientific theorems and rationales involved in AI which belong from GL, specifically the Chomsky School. It, thus, provides good evidence from syntax, semantics, language faculty, Universal Grammar, computational system of human language, language acquisition, human brain, programming languages (e.g. Python), Large Language Models, and unbiased AI scientists that this contribution is huge, and that this contribution cannot be denied. It concludes that however the huge GL contribution to AI, there are still points of divergence including the nature and type of language input.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 15 of its 101 references that are in the map. First posted on arXiv 26 Oct 2024.

Builds on

15 of 101 references.

References · 15

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2015Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Bookscited by 1,041
  4. 2023Instruction Tuning with GPT-4cited by 676
  5. 2016Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependenciescited by 350
  6. 2019What BERT is not: Lessons from a new suite of psycholinguistic diagnostics for language modelscited by 317
  7. 2018Colorless green recurrent networks dream hierarchicallycited by 210
  8. 2021Implicit Representations of Meaning in Neural Language Modelscited by 179
  9. 2023Is ChatGPT A Good Translator? Yes With GPT-4 As The Enginecited by 172
  10. 2020Syntactic Structure from Deep Learningcited by 99
  11. 2019On The Evaluation of Machine Translation Systems Trained With Back-Translationcited by 40
  12. 2019Still a Pain in the Neck: Evaluating Text Representations on Lexical Compositioncited by 27
3 more
  1. 2018Assessing Composition in Sentence Vector Representationscited by 26
  2. 2020Investigating Novel Verb Learning in BERT: Selectional Preference Classes and Alternation-Based Syntactic Generalizationcited by 16
  3. 2023Syntax-semantics interface: an algebraic modelcited by 6

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 4.

7 papers.