Tag
This paper applies hermeneutic philosophy to large language models to address interpretive risks like 'interpretive misplacement' and derives design principles for responsible human-AI co-interpretation in contexts such as law, education, and public discourse.
This paper introduces Augmented Sparse Encoding Models to interpret brain responses to language using sparse features from language models, validated on high-field 7T fMRI data. It recovers known neural tuning properties and discovers a new voxel population tuned to people-related content.
IdiomX is a large-scale multilingual benchmark for idiom understanding, retrieval, and interpretation, containing over 190K examples across English, Arabic, and French, with four tasks for evaluating language models on idiomatic expressions.
AI agents can now interpret ambiguous clauses in smart contracts, making dispute resolution viable for micro-transactions and expanding smart contracts beyond rigid if/then logic.