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Sai Sumedh R. Hindupur

2 accepted papers

2026

Priors in time: Missing inductive biases for language model interpretability

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…

Cited by 0SourcecodeScholar
2025

Projecting Assumptions: The Duality Between Sparse Autoencoders and Concept Geometry

NeurIPS 2025poster

Sparse Autoencoders (SAEs) are widely used to interpret neural networks by identifying meaningful concepts from their representations. However, do SAEs truly uncover all concepts a model relies on, or are they inherently biased toward certain kinds of concepts? We introduce a unified framework that…

Cited by 0SourceScholar