HiPC-QR: Hierarchical Prompt Chaining for Query Reformulation Article Swipe
Hua Yang
,
Haiyang Li
,
Teresa Gonçalves
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/info16090790
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/info16090790
Query reformulation techniques optimize user queries to better align with documents, thus improving the performance of Information Retrieval (IR) systems. Previous methods have primarily focused on query expansion using techniques such as synonym replacement to improve recall. With the rapid advancement of Large Language Models (LLMs), the knowledge embedded within these models has grown. Research in prompt engineering has introduced various methods, with prompt chaining proving particularly effective for complex tasks. Directly prompting LLMs to reformulate queries has become a viable approach. However, existing LLM-based prompt methods for query reformulation often introduce irrelevant content into reformulated queries, resulting in decreased retrieval precision and misalignment with user intent. We propose a novel approach called Hierarchical Prompt Chaining for Query Reformulation (HiPC-QR). HiPC-QR employs a two-step prompt chaining technique to extract keywords from the original query and refine its structure by filtering out non-essential keywords based on the user’s query intent. This process reduces the query’s restrictiveness while simultaneously expanding essential keywords to enhance retrieval effectiveness. We evaluated the effectiveness of HiPC-QR on two benchmark retrieval datasets, namely MS MARCO and TREC Deep Learning.The experimental results show that HiPC-QR outperforms existing query reformulation methods on large-scale datasets in terms of both recall@10 and MRR@10.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/info16090790
- https://www.mdpi.com/2078-2489/16/9/790/pdf?version=1757581697
- OA Status
- gold
- References
- 25
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4414129111
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Raw OpenAlex JSON
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https://openalex.org/W4414129111Canonical identifier for this work in OpenAlex
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https://doi.org/10.3390/info16090790Digital Object Identifier
- Title
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HiPC-QR: Hierarchical Prompt Chaining for Query ReformulationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-09-11Full publication date if available
- Authors
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Hua Yang, Haiyang Li, Teresa GonçalvesList of authors in order
- Landing page
-
https://doi.org/10.3390/info16090790Publisher landing page
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https://www.mdpi.com/2078-2489/16/9/790/pdf?version=1757581697Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2078-2489/16/9/790/pdf?version=1757581697Direct OA link when available
- Cited by
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0Total citation count in OpenAlex
- References (count)
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25Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.simultaneously | 156 |
| abstract_inverted_index.restrictiveness | 154 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5075065160, https://openalex.org/A5085523573 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I132586189, https://openalex.org/I21803372 |
| citation_normalized_percentile.value | 0.53898973 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |