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Brain-Aligned Language Models for Long-Range Language Understanding and Neuroscientific Insight

Objective

The BrainAlign project aims to revolutionize next-generation artificial intelligence (AI) models by aligning them closely with the way the human brain understands language. While AI systems for language understanding and generation have undergone much progress in recent years thanks to language models, these systems still face significant challenges, such as understanding human intent. Moreover, the successes have mostly stemmed from tremendous increases in model size, and continuing this trend demands unrealistic amounts of data, compute power, and energy.

One way forward is to look to the only system we trust to truly understand complex language: the human brain. Insights from brain functions have long inspired AI, but these insights took years to consolidate and even longer to transfer to AI. For brain functions that are uniquely human, such as understanding complex natural language, the lack of suitable animal model organisms limits the mechanistic insights that can be applied to AI.

The BrainAlign project presents a novel, data-driven solution that will develop brain-aligned language models by forcing their internal processing to closely reflect information sampled directly from the human brain, as humans read and listen to large amounts of every-day language. By integrating machine learning techniques with human neuroimaging and behavioral data from novel experimental paradigms, BrainAlign will develop next-generation models with a deeper, human-like understanding of language. Additionally, innovative interpretability methods will allow these models to serve as model organisms, revealing mechanisms that mirror human brain processing of language and massively enhancing our scientific knowledge of language in the brain.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2025-STG

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Host institution

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 494 075,00
Address
HOFGARTENSTRASSE 8
80539 MUNCHEN
Germany

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Region
Berlin Berlin Berlin
Activity type
Research Organisations
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 494 075,00

Beneficiaries (1)