activity
20232026
most citedOn the Foundations of Shortcut Learning

6 citations · 11 across the 21 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

Language Model Activations Inhabit Privileged Error-Correcting Basins

Matthew Finlayson, Francisco Pernice, Eric Todd +16

Language models exhibit remarkable robustness, continuing to produce coherent text even when their activations are perturbed by interventions like linear steering. We hypothesize t…

cs.AI2026

The Independence Prior of SAEs Fragments Visual Concepts

Tommaso Mencattini, Giorgos Nikolaou, Donato Crisostomi +4

Sparse Autoencoders (SAEs) decompose model activations into sparse combinations of interpretable dictionary atoms. Although SAEs are grounded in the Linear Representation Hypothesi…

cs.AI2026

The Case for Model Science: Verify, Explore, Steer, Refine

Przemyslaw Biecek, Luca Longo, Jianlong Zhou +3

We argue that the AI community is now ready to move beyond benchmarking and consolidate scattered efforts in model analysis into a systematic discipline, a direction we term Model…

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.AI2025

A Geometric Unification of Concept Learning with Concept Cones

Alexandre Rocchi, Thomas Fel, Gianni Franchi

Two traditions of interpretability have evolved side by side but seldom spoken to each other: Concept Bottleneck Models (CBMs), which prescribe what a concept should be, and Sparse…