Papers with commercial search engines
Query Variant Detection Using Retriever as Environment (2025.naacl-industry)
Copied to clipboard
| Challenge: | Identifying query variants is nontrivial as highly similar query pairs may fail to differ in word form, order, or phrasing despite sharing the same intent. |
| Approach: | They propose to use retrieval as an environment feedback to capture semantic equivalence . experimental results demonstrate the efficacy of the proposed method . |
| Outcome: | The proposed method improves query variant detection across diverse scenarios. |
CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial Search (2025.naacl-industry)
Copied to clipboard
Kaixin Wu, Yixin Ji, Zeyuan Chen, Qiang Wang, Cunxiang Wang, Hong Liu, Baijun Ji, Xu Jia, Zhongyi Liu, Jinjie Gu, Yuan Zhou, Linjian Mo
| Challenge: | Relevance modeling between queries and items is a key component of commercial search engines. |
| Approach: | They propose a framework for continual pre-training of LLMs to enhance domain knowledge . they employ queries and multi-field item to jointly pre-train for enhancing domain knowledge. |
| Outcome: | The proposed model achieves convincing performance compared to strong baselines. |
WIKIR: A Python Toolkit for Building a Large-scale Wikipedia-based English Information Retrieval Dataset (2020.lrec-1)
Copied to clipboard
| Challenge: | ad-hoc information retrieval methods usually require large amounts of annotated data to be effective. |
| Approach: | They propose an open-source toolkit to automatically build large-scale English information retrieval datasets based on Wikipedia. |
| Outcome: | The proposed toolkit builds large-scale English information retrieval datasets based on Wikipedia with 59,252 queries and 2,617,003 pairs. |
Enabling Large Language Models to Generate Text with Citations (2023.emnlp-main)
Copied to clipboard
| Challenge: | Existing work relies on commercial search engines and human evaluation, making it difficult to reproduce and compare different modeling approaches. |
| Approach: | They propose a new generation paradigm that requires large language models to provide citations to one or a few text passages for any statement they generate. |
| Outcome: | The proposed model improves factual correctness and verifiability of large language models by providing citations to a set of questions and retrieval corpora and generating answers with citation. |
LitSearch: A Retrieval Benchmark for Scientific Literature Search (2024.emnlp-main)
Copied to clipboard
| Challenge: | Literature search questions pose significant challenges for modern retrieval systems . a lack of domain expertise and reasoning through lengthy papers is a challenge . |
| Approach: | They propose a retrieval benchmark for literature search queries using inline citations from papers and questions about recently published papers. |
| Outcome: | The proposed retrieval benchmarks outperform state-of-the-art retrieval models and reranking pipelines. |