ContextCite: Attributing Model Generation to Context

Published: 28 Jun 2024, Last Modified: 25 Jul 2024NextGenAISafety 2024 PosterEveryoneRevisionsBibTeXCC BY 4.0
Keywords: attribution, citation, generative models, large language models
TL;DR: We introduce ContextCite, a simple and scalable method to identify the parts of the context that are responsible for a language model generating a particular statement.
Abstract: How do language models actually *use* information provided as context when generating a response? Can we infer whether a particular generated statement is actually grounded in the context, a misinterpretation, or fabricated? To help answer these questions, we introduce the problem of *context attribution*: pinpointing the parts of the context (if any) that *led* a model to generate a particular statement. We then present ContextCite, a simple and scalable method for context attribution that can be applied on top of any existing language model.
Submission Number: 75
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