mlsanityData to 14 Oct 2026

Gold: A Global and Local-aware Denoising Framework for Commonsense Knowledge Graph Noise Detection

arXiv 2310.12011 ↗First posted 18 Oct 2023cs.CLcited by 4

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

Commonsense Knowledge Graphs (CSKGs) are crucial for commonsense reasoning, yet constructing them through human annotations can be costly. As a result, various automatic methods have been proposed to construct CSKG with larger semantic coverage. However, these unsupervised approaches introduce spurious noise that can lower the quality of the resulting CSKG, which cannot be tackled easily by existing denoising algorithms due to the unique characteristics of nodes and structures in CSKGs. To address this issue, we propose Gold (Global and Local-aware Denoising), a denoising framework for CSKGs that incorporates entity semantic information, global rules, and local structural information from the CSKG. Experiment results demonstrate that Gold outperforms all baseline methods in noise detection tasks on synthetic noisy CSKG benchmarks. Furthermore, we show that denoising a real-world CSKG is effective and even benefits the downstream zero-shot commonsense question-answering task.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 46 of its 81 references that are in the map. First posted on arXiv 18 Oct 2023.

Builds on

46 of 81 references.

Closest ancestors · 5

Same direction, newest first

  1. 2023CAR: Conceptualization-Augmented Reasoner for Zero-Shot Commonsense Question Answering24 May
  2. 2023CAT: A Contextualized Conceptualization and Instantiation Framework for Commonsense Reasoning8 May
  3. 2023CKBP v2: Better Annotation and Reasoning for Commonsense Knowledge Base Population20 Apr
  4. 2022MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation14 Oct
  5. 2022Acquiring and Modelling Abstract Commonsense Knowledge via Conceptualization3 Jun

Other references · 41

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2022Training language models to follow instructions with human feedbackcited by 15,971
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  5. 2017Graph Attention Networkscited by 8,923
  6. 2019PIQA: Reasoning about Physical Commonsense in Natural Languagecited by 2,883
  7. 2018CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledgecited by 1,822
  8. 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,254
  9. 2016ConceptNet 5.5: An Open Multilingual Graph of General Knowledgecited by 1,067
  10. 2014Embedding Entities and Relations for Learning and Inference in Knowledge Basescited by 932
  11. 2016Complex Embeddings for Simple Link Predictioncited by 902
  12. 2019RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Spacecited by 898
29 more
  1. 2021Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Modelscited by 463
  2. 2019COMET: Commonsense Transformers for Automatic Knowledge Graph Constructioncited by 450
  3. 2019KG-BERT: BERT for Knowledge Graph Completioncited by 324
  4. 2019Abductive Commonsense Reasoningcited by 301
  5. 2021Symbolic Knowledge Distillation: from General Language Models to Commonsense Modelscited by 270
  6. 2019DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphscited by 175
  7. 2022Deep Bidirectional Language-Knowledge Graph Pretrainingcited by 156
  8. 2020RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphscited by 118
  9. 2020GLUCOSE: GeneraLized and COntextualized Story Explanationscited by 86
  10. 2019Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoningcited by 63
  11. 2019Commonsense Knowledge Base Completion with Structural and Semantic Contextcited by 61
  12. 2019Grounded Conversation Generation as Guided Traverses in Commonsense Knowledge Graphscited by 59
  13. 2015Modeling Relation Paths for Representation Learning of Knowledge Basescited by 56
  14. 2017Knowledge Graph Embedding with Iterative Guidance from Soft Rulescited by 51
  15. 2023ChatGPT Evaluation on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relationscited by 40
  16. 2019Data Poisoning Attack against Knowledge Graph Embeddingcited by 36
  17. 2023Say What You Mean! Large Language Models Speak Too Positively about Negative Commonsense Knowledgecited by 32
  18. 2021ASER: Towards Large-scale Commonsense Knowledge Acquisition via Higher-order Selectional Preference over Eventualitiescited by 28
  19. 2021DISCOS: Bridging the Gap between Discourse Knowledge and Commonsense Knowledgecited by 26
  20. 2020Inductive Learning on Commonsense Knowledge Graph Completioncited by 22
  21. 2023Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraintscited by 21
  22. 2023Neural Compositional Rule Learning for Knowledge Graph Reasoningcited by 20
  23. 2018Triple Trustworthiness Measurement for Knowledge Graphcited by 16
  24. 2021Benchmarking Commonsense Knowledge Base Population with an Effective Evaluation Datasetcited by 15
  25. 2017Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidencecited by 14
  26. 2020What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarizationcited by 9
  27. 2020NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge Basescited by 9
  28. 2020KGClean: An Embedding Powered Knowledge Graph Cleaning Frameworkcited by 4
  29. 2023Mapping and Cleaning Open Commonsense Knowledge Bases with Generative Translationcited by 2

Built on by

Cited by year

Citing papers per year: 2024: 2; 2025: 2.

4 papers.

  1. 2024On the Role of Entity and Event Level Conceptualization in Generalizable Reasoning: A Survey of Tasks, Methods, Applications, and Future Directionscited by 3
  2. 2024KNOWCOMP POKEMON Team at DialAM-2024: A Two-Stage Pipeline for Detecting Relations in Dialogical Argument Miningcited by 2
  3. 2025Structuring the Unstructured: A Systematic Review of Text-to-Structure Generation for Agentic AI with a Universal Evaluation Frameworkcited by 2
  4. 2025Type Information-Assisted Self-Supervised Knowledge Graph Denoisingcited by 0

Similar, not cited

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  1. 2026Semantic Reasoning Denoising: Correcting Language Model Reasoning with Semantic Operators
  2. 2025When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables
  3. 2025Less is More: Denoising Knowledge Graphs For Retrieval Augmented Generation
  4. 2024LINKED: Eliciting, Filtering and Integrating Knowledge in Large Language Model for Commonsense Reasoning
  5. 2022Great Truths are Always Simple: A Rather Simple Knowledge Encoder for Enhancing the Commonsense Reasoning Capacity of Pre-Trained Models
  6. 2023Towards Faithful Knowledge Graph Explanation Through Deep Alignment in Commonsense Question Answering
  7. 2022Evaluate Confidence Instead of Perplexity for Zero-shot Commonsense Reasoning
  8. 2025DANS-KGC: Diffusion Based Adaptive Negative Sampling for Knowledge Graph Completion