I ter CQR : Iterative Conversational Query Reformulation with Retrieval Guidance (2024)

Abstract: Conversational search aims to retrieve passages containing essential information to answer queries in a multi-turn conversation. In conversational search, reformulating context-dependent conversational queries into stand-alone forms is imperative to effectively utilize off-the-shelf retrievers. Previous methodologies for conversational query reformulation frequently depend on human-annotated rewrites.However, these manually crafted queries often result in sub-optimal retrieval performance and require high collection costs.To address these challenges, we propose **Iter**ative **C**onversational **Q**uery **R**eformulation (**IterCQR**), a methodology that conducts query reformulation without relying on human rewrites. IterCQR iteratively trains the conversational query reformulation (CQR) model by directly leveraging information retrieval (IR) signals as a reward.Our IterCQR training guides the CQR model such that generated queries contain necessary information from the previous dialogue context.Our proposed method shows state-of-the-art performance on two widely-used datasets, demonstrating its effectiveness on both sparse and dense retrievers. Moreover, IterCQR exhibits superior performance in challenging settings such as generalization on unseen datasets and low-resource scenarios.

## introduction in the conversational question answering (cqa) task, questions and answers are exchanged in a multi-turn conversation. as a component of cqa task, conversational search aims to retrieve passages that contain the necessary information to answer the current query within the conversation @xcite . owing to the conversational setting, queries in cqa suffer from a high dependency on the pre-where does the energy from the hoover dam go? the dam's generators provide power for public and private utilities in nevada, arizona, and california. in the black canyon of the colorado river on the border between the u.s. states of nevada and arizona. hoover dam is a concrete archgravity dam in the black canyon of the colorado river, on the border between the u.s. states of nevada and arizona. ... ## analysis we analyze the effect of iterative rewriting on iter-cqr by each iteration. for each iteration, we measure the retrieval performance, token length of the rewritten queries, token overlap with the historical context, and token overlap with the gold passage. ## conclusion in this work, we propose itercqr, a methodology that iteratively improves cqr model without relying on human rewrites. itercqr leverages retrieval signals when training cqr model, which provides retriever-friendly guidance for cqr. we demonstrate the effectiveness of itercqr through state-of-the-art performance on the qrecc and topiocqa datasets. in addition, the experimental results indicate that itercqr learns to summarize previous contextual history, which leads to improved retrieval performance as the iteration progresses. furthermore, itercqr exhibits superior performance in challenging settings such as generalization on unseen datasets and low-resource setting.