1 citations · 1 across the 3 of their papers we have counts for
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Causality Invariance: Function and Concept Vectors in LLMs
Gustaw Opiełka, Hannes Rosenbusch, Claire E. Stevenson
Do large language models (LLMs) represent concepts abstractly, i.e., independent of input format? We revisit Function Vectors (FVs), compact representations of in-context learning…
Analogical Reasoning Inside Large Language Models: Concept Vectors and the Limits of Abstraction
Gustaw Opiełka, Hannes Rosenbusch, Claire E. Stevenson
Analogical reasoning relies on conceptual abstractions, but it is unclear whether Large Language Models (LLMs) harbor such internal representations. We explore distilled representa…
Do Large Language Models Solve ARC Visual Analogies Like People Do?
Gustaw Opiełka, Hannes Rosenbusch, Veerle Vijverberg +1
The Abstraction Reasoning Corpus (ARC) is a visual analogical reasoning test designed for humans and machines (Chollet, 2019). We compared human and large language model (LLM) perf…