More Room for Language: Investigating the Effect of Retrieval on Language Models

• URL: http://arxiv.org/abs/2404.10939v1
• Date: Tue, 16 Apr 2024 22:43:48 GMT
• Title: More Room for Language: Investigating the Effect of Retrieval on Language Models
• Authors: David Samuel, Lucas Georges Gabriel Charpentier, Sondre Wold,
• Abstract summary: We introduce an 'ideal retrieval' methodology to study these models in a fully controllable setting. We conduct an evaluation to examine how retrieval augmentation affects the behavior of the underlying language model.
• Score: 3.8574940917179164
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Retrieval-augmented language models pose a promising alternative to standard language modeling. During pretraining, these models search in a corpus of documents for contextually relevant information that could aid the language modeling objective. We introduce an 'ideal retrieval' methodology to study these models in a fully controllable setting. We conduct an extensive evaluation to examine how retrieval augmentation affects the behavior of the underlying language model. Among other things, we observe that these models: i) save substantially less world knowledge in their weights, ii) are better at understanding local context and inter-word dependencies, but iii) are worse at comprehending global context.

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