Papers with knowledge infusion mechanism

1 papers
ConvGQR: Generative Query Reformulation for Conversational Search (2023.acl-long)

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Challenge: Existing methods to determine a good search query from the whole conversation context are expensive and often lead to sub-optimal results.
Approach: They propose a framework to reformulate conversational queries based on generative pre-trained language models (PLMs) they propose generative knowledge infusion mechanism to optimize query reformulation and retrieval.
Outcome: Extensive experiments on four conversational search datasets demonstrate the effectiveness of ConvGQR.

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