most citedFailures and Successes to Learn a Core Conceptual Distinction from the Statistics of Language

5 citations · 5 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL20265 cited

Failures and Successes to Learn a Core Conceptual Distinction from the Statistics of Language

Zhimin Hu, Jeroen van Paridon, Gary Lupyan

Generic statements like "tigers are striped" and "cars have radios" communicate information that is, in general, true. However, while the first statement is true in principle, the…

cs.AI2026

Reasoning as Pattern Matching: Shared Mechanisms in Human and LLM Everyday Reasoning

Zach Studdiford, Gary Lupyan

When large language models (LLMs) fail to generalize or make haphazard errors in reasoning, it is often taken as evidence that LLMs are not truly reasoning, but rather performing a…

cs.CL2026

The Astonishing Ability of Large Language Models to Parse Jabberwockified Language

Gary Lupyan, Senyi Yang

We show that large language models (LLMs) have an astonishing ability to recover meaning from severely degraded English texts. Texts in which content words have been randomly subst…

cs.CL2026

The unreasonable effectiveness of pattern matching

Gary Lupyan, Blaise Agüera y Arcas

We report on an astonishing ability of large language models (LLMs) to make sense of "Jabberwocky" language in which most or all content words have been randomly replaced by nonsen…

cs.CL2025

Large language models have learned to use language

Gary Lupyan

Acknowledging that large language models have learned to use language can open doors to breakthrough language science. Achieving these breakthroughs may require abandoning some lon…

cs.CL2025

How important is language for human-like intelligence?

Gary Lupyan, Hunter Gentry, Martin Zettersten

We use language to communicate our thoughts. But is language merely the expression of thoughts, which are themselves produced by other, nonlinguistic parts of our minds? Or does la…