mlsanityData to 14 Oct 2026

Text-to-Text Multi-view Learning for Passage Re-ranking

arXiv 2104.14133 ↗First posted 29 Apr 2021cs.IR cs.CLcited by 14

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Abstract (arXiv)

Recently, much progress in natural language processing has been driven by deep contextualized representations pretrained on large corpora. Typically, the fine-tuning on these pretrained models for a specific downstream task is based on single-view learning, which is however inadequate as a sentence can be interpreted differently from different perspectives. Therefore, in this work, we propose a text-to-text multi-view learning framework by incorporating an additional view -- the text generation view -- into a typical single-view passage ranking model. Empirically, the proposed approach is of help to the ranking performance compared to its single-view counterpart. Ablation studies are also reported in the paper.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 20 of its 28 references that are in the map. First posted on arXiv 29 Apr 2021.

Builds on

20 of 28 references.

References · 20

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  5. 2020Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inferencecited by 938
  6. 2020It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learnerscited by 669
  7. 2019Passage Re-ranking with BERTcited by 645
  8. 2015Multi-view Convolutional Neural Networks for 3D Shape Recognitioncited by 565
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  10. 2020Pretrained Transformers for Text Ranking: BERT and Beyondcited by 267
  11. 2019Massively Multilingual Neural Machine Translationcited by 246
  12. 2019Document Expansion by Query Predictioncited by 231
8 more
  1. 2019Multi-Stage Document Ranking with BERTcited by 201
  2. 2017A Deep Relevance Matching Model for Ad-hoc Retrievalcited by 126
  3. 2016A Survey of Multi-View Representation Learningcited by 107
  4. 2017End-to-End Neural Ad-hoc Ranking with Kernel Poolingcited by 85
  5. 2016Learning to Match Using Local and Distributed Representations of Text for Web Searchcited by 68
  6. 2020Interpretable & Time-Budget-Constrained Contextualization for Re-Rankingcited by 21
  7. 2020Chatbot Interaction with Artificial Intelligence: Human Data Augmentation with T5 and Language Transformer Ensemble for Text Classificationcited by 7
  8. 2019On the Effect of Low-Frequency Terms on Neural-IR Modelscited by 6

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Citing papers per year: 2022: 3; 2023: 5; 2024: 5; 2025: 1.

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  1. 2023Large Language Models for Information Retrieval: A Surveycited by 331
  2. 2022Improving Passage Retrieval with Zero-Shot Question Generationcited by 165
  3. 2022RankT5: Fine-Tuning T5 for Text Ranking with Ranking Lossescited by 115
  4. 2023Leveraging Large Language Models in Conversational Recommender Systemscited by 63
  5. 2024Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generationcited by 27
  6. 2023Discrete Prompt Optimization via Constrained Generation for Zero-shot Re-rankercited by 20
  7. 2024Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as Rankerscited by 17
  8. 2022ED2LM: Encoder-Decoder to Language Model for Faster Document Re-ranking Inferencecited by 9
  9. 2024Self-Calibrated Listwise Reranking with Large Language Modelscited by 7
  10. 2024Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language Modelscited by 4
  11. 2024Entity Insertion in Multilingual Linked Corpora: The Case of Wikipediacited by 3
  12. 2025The Evolution of Reranking Models in Information Retrieval: From Heuristic Methods to Large Language Modelscited by 3
2 more
  1. 2023Improving Zero-shot Reader by Reducing Distractions from Irrelevant Documents in Open-Domain Question Answeringcited by 2
  2. 2023Empowering Language Model with Guided Knowledge Fusion for Biomedical Document Re-rankingcited by 0