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Sheridan Feucht

11 papers hereh-index 6132 citations14 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author6

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CL7
  • cs.LG2
  • cs.AI1
  • cs.CV1

identity via Semantic Scholar / OpenAlex

activity
20212026
most citedDeep Neural Networks Can Learn Generalizable Same-Different Visual Relations

2 citations · 2 across the 10 of their papers we have counts for

collaborators
Showing 2026Show all

3 papers · 1 filter

cs.LG2026

Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behavior

Daniel Wurgaft, Can Rager, Matthew Kowal +13

Neural representations carry rich geometric structure; but does that structure causally shape behavior? To address this question, we intervene along paths through activation space…

cs.AI2026

Arithmetic in the Wild: Llama uses Base-10 Addition to Reason About Cyclic Concepts

Sheridan Feucht, Tal Haklay, Usha Bhalla +9

Does structure in representations imply structure in computation? We study how Llama-3.1-8B reasons over cyclic concepts (e.g., "what month is six months after August?"). Even thou…

cs.LG2026

Do Sparse Autoencoders Capture Concept Manifolds?

Usha Bhalla, Thomas Fel, Can Rager +9

Sparse autoencoders (SAEs) are widely used to extract interpretable features from neural network representations, often under the implicit assumption that concepts correspond to in…

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