Papers by Anupam Samanta

1 papers
QUILL: Query Intent with Large Language Models using Retrieval Augmentation and Multi-stage Distillation (2022.emnlp-industry)

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Challenge: Large Language Models (LLMs) have shown impressive results on a variety of text understanding tasks.
Approach: They propose a two-stage distillation approach that allows retrieval augmentation to be carried over without the increased compute associated with it.
Outcome: The proposed approach can carry over the gains of retrieval augmentation without suffering the increased compute typically associated with it.

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