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20242026
most citedHow Causal Abstraction Underpins Computational Explanation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

7 papers

cs.LG20261 cited

How Causal Abstraction Underpins Computational Explanation

Atticus Geiger, Jacqueline Harding, Thomas Icard

Explanations of cognitive behavior often appeal to computations over representations. What does it take for a system to implement a given computation over suitable representational…

cs.MA2026

A Communication-First Account of Explanation

Jacqueline Harding, Tobias Gerstenberg, Thomas Icard

This paper develops a formal account of causal explanation, grounded in a theory of conversational pragmatics, and inspired by the interventionist idea that explanation is about as…

cs.CL2026

Evaluating Commercial AI Chatbots as News Intermediaries

Mirac Suzgun, Emily Shen, Federico Bianchi +5

AI chatbots are rapidly shaping how people encounter the news, yet no prior study has systematically measured how accurately these systems, with their proprietary search integratio…

cs.LG2026

Transcoder Adapters for Reasoning-Model Diffing

Nathan Hu, Jake Ward, Thomas Icard +1

While reasoning models are increasingly ubiquitous, the effects of reasoning training on a model's internal mechanisms remain poorly understood. In this work, we introduce transcod…

cs.LG2025

Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution Behaviors

Jing Huang, Junyi Tao, Thomas Icard +2

Interpretability research now offers a variety of techniques for identifying abstract internal mechanisms in neural networks. Can such techniques be used to predict how models will…

cs.CY2025

Modeling Discrimination with Causal Abstraction

Milan Mossé, Kara Schechtman, Frederick Eberhardt +1

A person is directly racially discriminated against only if her race caused her worse treatment. This implies that race is an attribute sufficiently separable from other attributes…