7 citations · 13 across the 7 of their papers we have counts for
7 papers
Post-training makes large language models less human-like
Marcel Binz, Elif Akata, Abdullah Almaatouq +76
Large language models (LLMs) are increasingly used as surrogates for human participants, but it remains unclear which models best capture human behavior and why. To address this, w…
Tracing the ongoing emergence of human-like reasoning in Large Language Models
Paolo Morosi, Nikoleta Pantelidou, Fritz Günther +2
Humans effortlessly go beyond literal meanings: If you mow the lawn, I will give you fifty dollars, is typically understood as implying that the speaker will pay only if the lawn i…
Multilingual Large Language Models do not comprehend all natural languages to equal degrees
Natalia Moskvina, Raquel Montero, Masaya Yoshida +8
Large Language Models (LLMs) play a critical role in how humans access information. While their core use relies on comprehending written requests, our understanding of this ability…
Large Language Model probabilities cannot reliably distinguish between possible and impossible language
Evelina Leivada, Raquel Montero, Paolo Morosi +5
A controversial test for Large Language Models concerns the ability to discern possible from impossible language. While some evidence attests to the models sensitivity to what cros…
When Large Language Models are More PersuasiveThan Incentivized Humans, and Why
Jiacheng Liu, Francesco Salvi, Philipp Schoenegger +37
Large Language Models (LLMs) have been shown to be highly persuasive, but when and why they outperform humans is still an open question. We compare the persuasiveness of two LLMs (…
Fundamental Principles of Linguistic Structure are Not Represented by o3
Elliot Murphy, Evelina Leivada, Vittoria Dentella +2
A core component of a successful artificial general intelligence would be the rapid creation and manipulation of grounded compositional abstractions and the demonstration of expert…
Language in Vivo vs. in Silico: Size Matters but Larger Language Models Still Do Not Comprehend Language on a Par with Humans Due to Impenetrable Semantic Reference
Vittoria Dentella, Fritz Guenther, Evelina Leivada
Understanding the limits of language is a prerequisite for Large Language Models (LLMs) to act as theories of natural language. LLM performance in some language tasks presents both…