Cover Image

On the referential capacity of language models: An internalist rejoinder to Mandelkern & Linzen

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Baggio, Giosue, Murphy, Elliot
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Shadow of the (Hierarchical) Tree: Reconciling Symbolic and Predictive Components of the Neural Code for Syntax
by: Murphy, Elliot
Published: (2024)

What is a word?
by: Murphy, Elliot
Published: (2024)

Frege in the Flesh: Biolinguistics and the Neural Enforcement of Syntactic Structures
by: Murphy, Elliot
Published: (2026)

Merge-based syntax is mediated by distinct neurocognitive mechanisms: A clustering analysis of comprehension abilities in 84,000 individuals with language deficits across nine languages
by: Murphy, Elliot, et al.
Published: (2025)

Testing AI on language comprehension tasks reveals insensitivity to underlying meaning
by: Dentella, Vittoria, et al.
Published: (2023)

Neurocomputational Mechanisms of Syntactic Transfer in Bilingual Sentence Production
by: Uluslu, Ahmet Yavuz, et al.
Published: (2026)

A Comparative Investigation of Compositional Syntax and Semantics in DALL-E 2
by: Murphy, Elliot, et al.
Published: (2024)

A Sentence is Worth a Thousand Pictures: Can Large Language Models Understand Hum4n L4ngu4ge and the W0rld behind W0rds?
by: Leivada, Evelina, et al.
Published: (2023)

Fundamental Principles of Linguistic Structure are Not Represented by o3
by: Murphy, Elliot, et al.
Published: (2025)

Large language models have learned to use language
by: Lupyan, Gary
Published: (2025)

Tiny language models
by: Gross, Ronit D., et al.
Published: (2025)

Can we teach language models to gloss endangered languages?
by: Ginn, Michael, et al.
Published: (2024)

Retrieval augmentation of large language models for lay language generation
by: Guo, Yue, et al.
Published: (2022)

Do large language models resemble humans in language use?
by: Cai, Zhenguang G., et al.
Published: (2023)

Studies with impossible languages falsify LMs as models of human language
by: Bowers, Jeffrey S., et al.
Published: (2025)

Why do language models perform worse for morphologically complex languages?
by: Arnett, Catherine, et al.
Published: (2024)

Prompting language influences diagnostic reasoning and accuracy of large language models
by: Bazoge, Adrien, et al.
Published: (2026)

Large language models are not about natural language
by: Bolhuis, Johan J., et al.
Published: (2025)

Dissociating language and thought in large language models
by: Mahowald, Kyle, et al.
Published: (2023)

Dynamic data sampler for cross-language transfer learning in large language models
by: Li, Yudong, et al.
Published: (2024)

InkubaLM: A small language model for low-resource African languages
by: Tonja, Atnafu Lambebo, et al.
Published: (2024)

Multilingual large language models leak human stereotypes across language boundaries
by: Cao, Yang Trista, et al.
Published: (2023)

Effective vocabulary expanding of multilingual language models for extremely low-resource languages
by: Zheng, Jianyu
Published: (2026)

Anthropocentric bias in language model evaluation
by: Millière, Raphaël, et al.
Published: (2024)

Open foundation models for Azerbaijani language
by: Isbarov, Jafar, et al.
Published: (2024)

Demystifying optimized prompts in language models
by: Melamed, Rimon, et al.
Published: (2025)

Why transformers are obviously good models of language
by: Hill, Felix
Published: (2024)

Oddballness: universal anomaly detection with language models
by: Graliński, Filip, et al.
Published: (2024)

Octopus v4: Graph of language models
by: Chen, Wei, et al.
Published: (2024)

How much do language models memorize?
by: Morris, John X., et al.
Published: (2025)

Universal computation is intrinsic to language model decoding
by: Lewandowski, Alex, et al.
Published: (2026)

Automata-based constraints for language model decoding
by: Koo, Terry, et al.
Published: (2024)

Humans overrely on overconfident language models, across languages
by: Rathi, Neil, et al.
Published: (2025)

World model inspired sarcasm reasoning with large language model agents
by: Inoshita, Keito, et al.
Published: (2025)

NLD-LLM: A systematic framework for evaluating small language transformer models on natural language description
by: Jelodar, Hamed, et al.
Published: (2025)

GRASP: A novel benchmark for evaluating language GRounding And Situated Physics understanding in multimodal language models
by: Jassim, Serwan, et al.
Published: (2023)

Fluent dreaming for language models
by: Thompson, T. Ben, et al.
Published: (2024)

Algorithmic progress in language models
by: Ho, Anson, et al.
Published: (2024)

Efficient transformer with reinforced position embedding for language models
by: Hsiao, Yen-Che, et al.
Published: (2024)

Measuring short-form factuality in large language models
by: Wei, Jason, et al.
Published: (2024)