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Margin-Regularized Structured Semantic Alignment for Brain-Language Correspondence
Not provided in the abstract
brain-language decodingsemantic alignmentcontrastive learningneural representations
2608.16975
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2h ago70%
Abstract
This paper proposes a framework for aligning brain embeddings with text embeddings to improve brain-language decoding interpretability.
Reality Card
Core Claim
The proposed MD-SigLIP framework enables explicit modeling of the correspondence between neural representations and language semantics, achieving state-of-the-art retrieval performance.
Method / Result
Achieved state-of-the-art retrieval performance under both full-vocabulary and subset evaluation settings.
Limitations
The abstract does not specify limitations or reproducibility concerns.
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