mlsanityData to 7 Oct 2026

Text Matching as Image Recognition

arXiv 1602.06359 ↗First posted 20 Feb 2016cs.CL cs.AIcited by 59

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Abstract (arXiv)

Matching two texts is a fundamental problem in many natural language processing tasks. An effective way is to extract meaningful matching patterns from words, phrases, and sentences to produce the matching score. Inspired by the success of convolutional neural network in image recognition, where neurons can capture many complicated patterns based on the extracted elementary visual patterns such as oriented edges and corners, we propose to model text matching as the problem of image recognition. Firstly, a matching matrix whose entries represent the similarities between words is constructed and viewed as an image. Then a convolutional neural network is utilized to capture rich matching patterns in a layer-by-layer way. We show that by resembling the compositional hierarchies of patterns in image recognition, our model can successfully identify salient signals such as n-gram and n-term matchings. Experimental results demonstrate its superiority against the baselines.

Key facts. Cited by 59 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Feb 2016.

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Citing papers per year: 2021: 17; 2022: 13; 2023: 13; 2024: 10; 2025: 6.

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  2. 2023LLMDet: A Third Party Large Language Models Generated Text Detection Toolcited by 44
  3. 2021Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankerscited by 34
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  7. 2021Learning Fine-grained Fact-Article Correspondence in Legal Casescited by 15
  8. 2021Dialogue History Matters! Personalized Response Selectionin Multi-turn Retrieval-based Chatbotscited by 14
  9. 2021Sentence Similarity Based on Contextscited by 12
  10. 2023BERM: Training the Balanced and Extractable Representation for Matching to Improve Generalization Ability of Dense Retrievalcited by 11
  11. 2022Match-Prompt: Improving Multi-task Generalization Ability for Neural Text Matching via Prompt Learningcited by 10
  12. 2021Graph-based Multilingual Product Retrieval in E-commerce Searchcited by 9
38 more
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  4. 2021Contrastive Document Representation Learning with Graph Attention Networkscited by 6
  5. 2024Efficient Document Ranking with Learnable Late Interactionscited by 6
  6. 2025Pathway to Relevance: How Cross-Encoders Implement a Semantic Variant of BM25cited by 6
  7. 2021Match-Ignition: Plugging PageRank into Transformer for Long-form Text Matchingcited by 5
  8. 2024Towards Boosting LLMs-driven Relevance Modeling with Progressive Retrieved Behavior-augmented Promptingcited by 5
  9. 2022A Transformer-Based Substitute Recommendation Model Incorporating Weakly Supervised Customer Behavior Datacited by 4
  10. 2023Beyond Semantics: Learning a Behavior Augmented Relevance Model with Self-supervised Learningcited by 4
  11. 2024Deep Bag-of-Words Model: An Efficient and Interpretable Relevance Architecture for Chinese E-Commercecited by 4
  12. 2021On Length Divergence Bias in Textual Matching Modelscited by 3
  13. 2023Unified Embedding Based Personalized Retrieval in Etsy Searchcited by 3
  14. 2024Robust Interaction-Based Relevance Modeling for Online e-Commerce Searchcited by 3
  15. 2024Explainable LLM-driven Multi-dimensional Distillation for E-Commerce Relevance Learningcited by 3
  16. 2024Boosting LLM-based Relevance Modeling with Distribution-Aware Robust Learningcited by 3
  17. 2021Modeling Relevance Ranking under the Pre-training and Fine-tuning Paradigmcited by 2
  18. 2021Embracing Structure in Data for Billion-Scale Semantic Product Searchcited by 2
  19. 2022Two-stream Hierarchical Similarity Reasoning for Image-text Matchingcited by 2
  20. 2022HumanAL: Calibrating Human Matching Beyond a Single Taskcited by 2
  21. 2023LADER: Log-Augmented DEnse Retrieval for Biomedical Literature Searchcited by 2
  22. 2023SPM: Structured Pretraining and Matching Architectures for Relevance Modeling in Meituan Searchcited by 2
  23. 2024Neural Machine Unrankingcited by 2
  24. 2025ADORE: Autonomous Domain-Oriented Relevance Engine for E-commercecited by 2
  25. 2021TAG: Toward Accurate Social Media Content Tagging with a Concept Graphcited by 1
  26. 2022TeKo: Text-Rich Graph Neural Networks with External Knowledgecited by 1
  27. 2022Query-Response Interactions by Multi-tasks in Semantic Search for Chatbot Candidate Retrievalcited by 1
  28. 2022Legal Element-oriented Modeling with Multi-view Contrastive Learning for Legal Case Retrievalcited by 1
  29. 2022Towards Structure-aware Paraphrase Identification with Phrase Alignment Using Sentence Encoderscited by 1
  30. 2022Effective and Efficient Query-aware Snippet Extraction for Web Searchcited by 1
  31. 2023Cross-Model Comparative Loss for Enhancing Neuronal Utility in Language Understandingcited by 1
  32. 2023FCC: Fusing Conversation History and Candidate Provenance for Contextual Response Ranking in Dialogue Systemscited by 1
  33. 2024CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial Searchcited by 1
  34. 2021Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Searchcited by 0
  35. 2021Locate Who You Are: Matching Geo-location to Text for User Identity Linkagecited by 0
  36. 2021Toward the Understanding of Deep Text Matching Models for Information Retrievalcited by 0
  37. 2022Profiling and Evolution of Intellectual Propertycited by 0
  38. 2022Adaptable Text Matching via Meta-Weight Regulatorcited by 0

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