Itercqr: Iterative conversational query reformulation without human supervision

[PDF] arxiv.org

History-Aware Conversational Dense Retrieval

F Mo, C Qu, K Mao, T Zhu, Z Su, K Huang… - arXiv preprint arXiv …, 2024 - arxiv.org
Conversational search facilitates complex information retrieval by enabling multi-turn
interactions between users and the system. Supporting such interactions requires a …
被引用次数：11 相关文章 所有 2 个版本
[PDF] arxiv.org

Conv-coa: Improving open-domain question answering in large language models via conversational chain-of-action

Z Pan, H Luo, M Li, H Liu - arXiv preprint arXiv:2405.17822, 2024 - arxiv.org
We present a Conversational Chain-of-Action (Conv-CoA) framework for Open-domain
Conversational Question Answering (OCQA). Compared with literature, Conv-CoA …
被引用次数：6 相关文章 所有 2 个版本
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Ask Optimal Questions: Aligning Large Language Models with Retriever's Preference in Conversational Search

C Yoon, G Kim, B Jeon, S Kim, Y Jo, J Kang - arXiv preprint arXiv …, 2024 - arxiv.org
Conversational search, unlike single-turn retrieval tasks, requires understanding the current
question within a dialogue context. The common approach of rewrite-then-retrieve aims to …
被引用次数：4 相关文章 所有 2 个版本
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Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Search

F Mo, C Qu, K Mao, Y Wu, Z Su, K Huang… - arXiv preprint arXiv …, 2024 - arxiv.org
Conversational search supports multi-turn user-system interactions to solve complex
information needs. Different from the traditional single-turn ad-hoc search, conversational …
相关文章 所有 2 个版本
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CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Search

F Mo, A Ghaddar, K Mao, M Rezagholizadeh… - arXiv preprint arXiv …, 2024 - arxiv.org
In this paper, we study how open-source large language models (LLMs) can be effectively
deployed for improving query rewriting in conversational search, especially for ambiguous …
被引用次数：2 相关文章 所有 2 个版本
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Conversational Query Reformulation with the Guidance of Retrieved Documents

J Park, H Lee - arXiv preprint arXiv:2407.12363, 2024 - arxiv.org
Conversational search seeks to retrieve relevant passages for the given questions in
Conversational QA (ConvQA). Questions in ConvQA face challenges such as omissions and …
相关文章 所有 2 个版本
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AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignment

Y Lai, J Wu, C Zhang, H Sun, D Zhou - arXiv preprint arXiv:2407.01965, 2024 - arxiv.org
Conversational Query Reformulation (CQR) has significantly advanced in addressing the
challenges of conversational search, particularly those stemming from the latent user intent …
相关文章 所有 2 个版本