mlsanityData to 14 Oct 2026

HiURE: Hierarchical Exemplar Contrastive Learning for Unsupervised Relation Extraction

arXiv 2205.02225 ↗First posted 4 May 2022cs.CL cs.AIcited by 32

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Abstract (arXiv)

Unsupervised relation extraction aims to extract the relationship between entities from natural language sentences without prior information on relational scope or distribution. Existing works either utilize self-supervised schemes to refine relational feature signals by iteratively leveraging adaptive clustering and classification that provoke gradual drift problems, or adopt instance-wise contrastive learning which unreasonably pushes apart those sentence pairs that are semantically similar. To overcome these defects, we propose a novel contrastive learning framework named HiURE, which has the capability to derive hierarchical signals from relational feature space using cross hierarchy attention and effectively optimize relation representation of sentences under exemplar-wise contrastive learning. Experimental results on two public datasets demonstrate the advanced effectiveness and robustness of HiURE on unsupervised relation extraction when compared with state-of-the-art models.

Key facts. Cited by 32 papers in the map (data through 14 Oct 2026). Builds on 22 of its 59 references that are in the map. First posted on arXiv 4 May 2022.

Builds on

22 of 59 references.

References · 22

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
  3. 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,513
  4. 2020Unsupervised Learning of Visual Features by Contrasting Cluster Assignmentscited by 2,857
  5. 2018Unsupervised Feature Learning via Non-Parametric Instance-level Discriminationcited by 1,845
  6. 2016Understanding deep learning requires rethinking generalizationcited by 1,674
  7. 2018Deep Clustering for Unsupervised Learning of Visual Featurescited by 1,028
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  9. 2020Prototypical Contrastive Learning of Unsupervised Representationscited by 640
  10. 2019Matching the Blanks: Distributional Similarity for Relation Learningcited by 272
  11. 2020Online Deep Clustering for Unsupervised Representation Learningcited by 100
  12. 2020Learning from Context or Names? An Empirical Study on Neural Relation Extractioncited by 75
10 more
  1. 2018Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systemscited by 70
  2. 2014Question Answering with Subgraph Embeddingscited by 58
  3. 2018Self-supervised learning of a facial attribute embedding from videocited by 45
  4. 2020SelfORE: Self-supervised Relational Feature Learning for Open Relation Extractioncited by 43
  5. 2020Semi-supervised Relation Extraction via Incremental Meta Self-Trainingcited by 35
  6. 2021Gradient Imitation Reinforcement Learning for Low Resource Relation Extractioncited by 33
  7. 2022Graph Neural Network with Curriculum Learning for Imbalanced Node Classificationcited by 19
  8. 2022Pair-Level Supervised Contrastive Learning for Natural Language Inferencecited by 12
  9. 2020Revisiting Unsupervised Relation Extractioncited by 11
  10. 2021Element Intervention for Open Relation Extractioncited by 11

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 8; 2023: 14; 2024: 3; 2025: 2; 2026: 5.

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  1. 2022Character-level White-Box Adversarial Attacks against Transformers via Attachable Subwords Substitutioncited by 28
  2. 2022Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graphcited by 22
  3. 2023Unsupervised Entity Alignment for Temporal Knowledge Graphscited by 19
  4. 2023Read it Twice: Towards Faithfully Interpretable Fact Verification by Revisiting Evidencecited by 17
  5. 2025VLA-Mark: A cross modal watermark for large vision-language alignment modelcited by 12
  6. 2022Domain-Specific NER via Retrieving Correlated Samplescited by 11
  7. 2023GDA: Generative Data Augmentation Techniques for Relation Extraction Taskscited by 10
  8. 2023Improving Unsupervised Relation Extraction by Augmenting Diverse Sentence Pairscited by 10
  9. 2023RAPL: A Relation-Aware Prototype Learning Approach for Few-Shot Document-Level Relation Extractioncited by 9
  10. 2026Vision-Language Introspection: Mitigating Overconfident Hallucinations in MLLMs via Interpretable Bi-Causal Steeringcited by 8
  11. 2023Enhancing Cross-lingual Natural Language Inference by Soft Prompting with Multilingual Verbalizercited by 7
  12. 2023Multimodal Relation Extraction with Cross-Modal Retrieval and Synthesiscited by 7
20 more
  1. 2024HEX: Hierarchical Emergence Exploitation in Self-Supervised Algorithmscited by 7
  2. 2022Graph Component Contrastive Learning for Concept Relatedness Estimationcited by 6
  3. 2022Entity-to-Text based Data Augmentation for various Named Entity Recognition Taskscited by 6
  4. 2023Think Rationally about What You See: Continuous Rationale Extraction for Relation Extractioncited by 6
  5. 2022Query-based Instance Discrimination Network for Relational Triple Extractioncited by 5
  6. 2023Prompt Me Up: Unleashing the Power of Alignments for Multimodal Entity and Relation Extractioncited by 5
  7. 2023Give Me More Details: Improving Fact-Checking with Latent Retrievalcited by 4
  8. 2023Gaussian Prior Reinforcement Learning for Nested Named Entity Recognitioncited by 3
  9. 2024Taxes Are All You Need: Integration of Taxonomical Hierarchy Relationships into the Contrastive Losscited by 3
  10. 2026Distilling the Thought, Watermarking the Answer: A Principle Semantic Guided Watermark for Large Reasoning Modelscited by 3
  11. 2026A Visual Semantic Adaptive Watermark grounded by Prefix-Tuning for Large Vision-Language Modelcited by 3
  12. 2026Decoding by Perturbation: Mitigating MLLM Hallucinations via Dynamic Textual Perturbationcited by 3
  13. 2022Scene Graph Modification as Incremental Structure Expandingcited by 2
  14. 2023COMBO: A Complete Benchmark for Open KG Canonicalizationcited by 2
  15. 2023Exploring the Compositional Generalization in Context Dependent Text-to-SQL Parsingcited by 2
  16. 2023Siamese Representation Learning for Unsupervised Relation Extractioncited by 1
  17. 2025Towards a More Generalized Approach in Open Relation Extractioncited by 1
  18. 2022Gradient Imitation Reinforcement Learning for General Low-Resource Information Extractioncited by 0
  19. 2024BioNCERE: Non-Contrastive Enhancement For Relation Extraction In Biomedical Textscited by 0
  20. 2026ViCLSR: A Supervised Contrastive Learning Framework with Natural Language Inference for Natural Language Understanding Taskscited by 0