mlsanityData to 7 Oct 2026

Towards Better Web Search Performance: Pre-training, Fine-tuning and Learning to Rank

arXiv 2303.04710 ↗First posted 28 Feb 2023cs.IRcited by 17

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Abstract (arXiv)

This paper describes the approach of the THUIR team at the WSDM Cup 2023 Pre-training for Web Search task. This task requires the participant to rank the relevant documents for each query. We propose a new data pre-processing method and conduct pre-training and fine-tuning with the processed data. Moreover, we extract statistical, axiomatic, and semantic features to enhance the ranking performance. After the feature extraction, diverse learning-to-rank models are employed to merge those features. The experimental results show the superiority of our proposal. We finally achieve second place in this competition.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Feb 2023.

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Citing papers per year: 2023: 7; 2024: 7; 2025: 3.

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  1. 2025LLM Post-Training: A Deep Dive into Reasoning Large Language Modelscited by 129
  2. 2024Unsupervised Real-Time Hallucination Detection based on the Internal States of Large Language Modelscited by 84
  3. 2024DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Modelscited by 63
  4. 2023SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrievalcited by 61
  5. 2024When Search Engine Services meet Large Language Models: Visions and Challengescited by 59
  6. 2024Mitigating Entity-Level Hallucination in Large Language Modelscited by 17
  7. 2023THUIR@COLIEE 2023: Incorporating Structural Knowledge into Pre-trained Language Models for Legal Case Retrievalcited by 16
  8. 2023Constructing Tree-based Index for Efficient and Effective Dense Retrievalcited by 15
  9. 2023Wikiformer: Pre-training with Structured Information of Wikipedia for Ad-hoc Retrievalcited by 15
  10. 2025Joint Evaluation of Answer and Reasoning Consistency for Hallucination Detection in Large Reasoning Modelscited by 13
  11. 2024LeKUBE: A Legal Knowledge Update BEnchmarkcited by 12
  12. 2023THUIR@COLIEE 2023: More Parameters and Legal Knowledge for Legal Case Entailmentcited by 11
5 more
  1. 2024Unbiased Learning to Rank Meets Reality: Lessons from Baidu's Large-Scale Search Datasetcited by 10
  2. 2024STARD: A Chinese Statute Retrieval Dataset with Real Queries Issued by Non-professionalscited by 10
  3. 2023An Intent Taxonomy of Legal Case Retrievalcited by 6
  4. 2023Pretrained deep models outperform GBDTs in Learning-To-Rank under label scarcitycited by 1
  5. 2025Industry Insights from Comparing Deep Learning and GBDT Models for E-Commerce Learning-to-Rankcited by 0