activity
20222026
most citedTesting AI on language comprehension tasks reveals insensitivity to underlying meaning

18 citations · 32 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Evidence and Intervention: A Coupled Active-Inference Extension of Rational Speech Act Models

Yonghyeon Gwon, Elliot Murphy, Chun Kee Chung

Identical utterance choices can arise from different communicative causes, and identical interpretations can leave different traces in what a listener learns. Rational Speech Act (…

cs.CL2026

No country for old linguists: LLM-brain alignment underdetermines neural computation

Elliot Murphy

Nastase et al. (2026) argue that large language models (LLMs) may illuminate language processing because both rely on distributed, context-sensitive representations shaped by stati…

cs.CL2023★ 18 cited

Testing AI on language comprehension tasks reveals insensitivity to underlying meaning

Vittoria Dentella, Fritz Guenther, Elliot Murphy +2

Large Language Models (LLMs) are recruited in applications that span from clinical assistance and legal support to question answering and education. Their success in specialized ta…

cs.CL2022★ 2 cited

Natural Language Syntax Complies with the Free-Energy Principle

Elliot Murphy, Emma Holmes, Karl Friston

Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-…

cs.CL2022★ 12 cited

DALL-E 2 Fails to Reliably Capture Common Syntactic Processes

Evelina Leivada, Elliot Murphy, Gary Marcus

Machine intelligence is increasingly being linked to claims about sentience, language processing, and an ability to comprehend and transform natural language into a range of stimul…