54 citations · 76 across the 6 of their papers we have counts for
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cs.IR2023
Look Before You Leap: A Universal Emergent Decomposition of Retrieval Tasks in Language Models
Alexandre Variengien, Eric Winsor
When solving challenging problems, language models (LMs) are able to identify relevant information from long and complicated contexts. To study how LMs solve retrieval tasks in div…
cs.CL2023★ 14 cited
How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model
Michael Hanna, Ollie Liu, Alexandre Variengien
Pre-trained language models can be surprisingly adept at tasks they were not explicitly trained on, but how they implement these capabilities is poorly understood. In this paper, w…