mlsanityData to 7 Oct 2026

Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance

arXiv 1909.02768 ↗First posted 6 Sep 2019cs.IR cs.LG stat.MLcited by 13

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Abstract (arXiv)

We present a pairwise learning to rank approach based on a neural net, called DirectRanker, that generalizes the RankNet architecture. We show mathematically that our model is reflexive, antisymmetric, and transitive allowing for simplified training and improved performance. Experimental results on the LETOR MSLR-WEB10K, MQ2007 and MQ2008 datasets show that our model outperforms numerous state-of-the-art methods, while being inherently simpler in structure and using a pairwise approach only.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Sep 2019.

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Citing papers per year: 2022: 4; 2023: 5; 2024: 1; 2025: 3.

13 papers.

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  1. 2022GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networkscited by 14
  2. 2024Offline Model-Based Optimization by Learning to Rankcited by 13
  3. 2023Learning to Compare Longitudinal Imagescited by 12
  4. 2023Multi-task Bioassay Pre-training for Protein-ligand Binding Affinity Predictioncited by 7
  5. 2022Rxn Hypergraph: a Hypergraph Attention Model for Chemical Reaction Representationcited by 6
  6. 2022Fair Interpretable Representation Learning with Correction Vectorscited by 3
  7. 2025The Evolution of Reranking Models in Information Retrieval: From Heuristic Methods to Large Language Modelscited by 3
  8. 2023Fine-grained Analysis of Non-parametric Estimation for Pairwise Learningcited by 2
  9. 2023Mobile Supply: The Last Piece of Jigsaw of Recommender Systemcited by 1
  10. 2025Mitigating Judgment Preference Bias in Large Language Models through Group-Based Pollingcited by 1
  11. 2022Evaluating Local Model-Agnostic Explanations of Learning to Rank Models with Decision Pathscited by 0
  12. 2023Perturbation-based Active Learning for Question Answeringcited by 0
1 more
  1. 2025Preference-based learning for news headline recommendationcited by 0