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Greta Tuckute

5 accepted papers

2026

Mixture of Cognitive Reasoners: Modular Reasoning with Brain-Like Specialization

Badr AlKhamissi, C. Nicolò De Sabbata, Greta Tuckute, Zeming Chen, Martin Schrimpf, Antoine Bosselut
ICLR 2026poster

Human cognitive behavior arises from the interaction of specialized brain networks dedicated to distinct functions, such as language, logic, and social reasoning. Inspired by this organization, we propose Mixture of Cognitive Reasoners (MiCRo): a modular, transformer-based architecture post-trained…

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2026

Priors in time: Missing inductive biases for language model interpretability

Ekdeep Singh Lubana, Sai Sumedh R. Hindupur, Can Rager, Valérie Costa, Oam Patel, Sonia Krishna Murthy +7
ICLR 2026poster

A central aim of interpretability tools applied to language models is to recover meaningful concepts from model activations. Existing feature extraction methods focus on single activations regardless of the context, implicitly assuming independence (and therefore stationarity). This leaves open whet…

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2025

From Language to Cognition: How LLMs Outgrow the Human Language Network

Badr AlKhamissi, Greta Tuckute, Yingtian Tang, Taha Osama A Binhuraib, Antoine Bosselut, Martin Schrimpf
EMNLP 2025

Large language models (LLMs) exhibit remarkable similarity to neural activity in the human language network. However, the key properties of language underlying this alignment—and how brain-like representations emerge and change across training—remain unclear. We here benchmark 34 training checkpoint

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2025

The LLM Language Network: A Neuroscientific Approach for Identifying Causally Task-Relevant Units

Badr AlKhamissi, Greta Tuckute, Antoine Bosselut, Martin Schrimpf
NAACL 2025long

Large language models (LLMs) exhibit remarkable capabilities on not just language tasks, but also various tasks that are not linguistic in nature, such as logical reasoning and social inference. In the human brain, neuroscience has identified a core language system that selectively and causally supp…

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2022

SentSpace: Large-Scale Benchmarking and Evaluation of Text using Cognitively Motivated Lexical, Syntactic, and Semantic Features

Greta Tuckute, Aalok Sathe, Mingye Wang, Harley Yoder, Cory Shain, Evelina Fedorenko
NAACL 2022system demonstrations

SentSpace is a modular framework for streamlined evaluation of text. SentSpacecharacterizes textual input using diverse lexical, syntactic, and semantic features derivedfrom corpora and psycholinguistic experiments. Core sentence features fall into three primaryfeature spaces: 1) Lexical, 2) Context…

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