mlsanityData to 7 Oct 2026

MIKE: A New Benchmark for Fine-grained Multimodal Entity Knowledge Editing

arXiv 2402.14835 ↗First posted 18 Feb 2024cs.CL cs.AI cs.LGcited by 25

On the map: Multimodal LLMs / vision-language models → Image editing and quality assessment

Abstract (arXiv)

Multimodal knowledge editing represents a critical advancement in enhancing the capabilities of Multimodal Large Language Models (MLLMs). Despite its potential, current benchmarks predominantly focus on coarse-grained knowledge, leaving the intricacies of fine-grained (FG) multimodal entity knowledge largely unexplored. This gap presents a notable challenge, as FG entity recognition is pivotal for the practical deployment and effectiveness of MLLMs in diverse real-world scenarios. To bridge this gap, we introduce MIKE, a comprehensive benchmark and dataset specifically designed for the FG multimodal entity knowledge editing. MIKE encompasses a suite of tasks tailored to assess different perspectives, including Vanilla Name Answering, Entity-Level Caption, and Complex-Scenario Recognition. In addition, a new form of knowledge editing, Multi-step Editing, is introduced to evaluate the editing efficiency. Through our extensive evaluations, we demonstrate that the current state-of-the-art methods face significant challenges in tackling our proposed benchmark, underscoring the complexity of FG knowledge editing in MLLMs. Our findings spotlight the urgent need for novel approaches in this domain, setting a clear agenda for future research and development efforts within the community.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Placed in Image editing and quality assessment, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 27 of its 44 references that are in the map. First posted on arXiv 18 Feb 2024.

Builds on

27 of 44 references.

References · 27

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2022Locating and Editing Factual Associations in GPTcited by 2,609
  5. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,231
  6. 2022Mass-Editing Memory in a Transformercited by 976
  7. 2021CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classificationcited by 806
  8. 2021Editing Factual Knowledge in Language Modelscited by 548
  9. 2023Otter: A Multi-Modal Model with In-Context Instruction Tuningcited by 548
  10. 2019Object Detection in 20 Years: A Surveycited by 528
  11. 2022Memory-Based Model Editing at Scalecited by 443
  12. 2023Editing Large Language Models: Problems, Methods, and Opportunitiescited by 367
15 more
  1. 2023RemoteCLIP: A Vision Language Foundation Model for Remote Sensingcited by 357
  2. 2023Can We Edit Factual Knowledge by In-Context Learning?cited by 284
  3. 2020Modifying Memories in Transformer Modelscited by 222
  4. 2023Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?cited by 203
  5. 2023Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entitiescited by 112
  6. 2022SmallCap: Lightweight Image Captioning Prompted with Retrieval Augmentationcited by 82
  7. 2022Repairing Neural Networks by Leaving the Right Past Behindcited by 27
  8. 2023Q: How to Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images!cited by 19
  9. 2023Fine-Grained Classification with Noisy Labelscited by 15
  10. 2022Personalizing Text-to-Image Generation via Aesthetic Gradientscited by 13
  11. 2022Show, Interpret and Tell: Entity-aware Contextualised Image Captioning in Wikipediacited by 10
  12. 2023MyStyle++: A Controllable Personalized Generative Priorcited by 8
  13. 2023Benchmarking Diverse-Modal Entity Linking with Generative Modelscited by 5
  14. 2021Show, Write, and Retrieve: Entity-aware Article Generation and Retrievalcited by 3
  15. 2023Few-shot Classification via Ensemble Learning with Multi-Order Statisticscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 10; 2025: 10; 2026: 5.

25 papers.

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  1. 2024A Survey on Evaluation of Multimodal Large Language Modelscited by 46
  2. 2024Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Modelscited by 44
  3. 2024Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Datasetcited by 29
  4. 2024Can Knowledge Editing Really Correct Hallucinations?cited by 28
  5. 2024A Survey on Multimodal Benchmarks: In the Era of Large AI Modelscited by 27
  6. 2024MC-MKE: A Fine-Grained Multimodal Knowledge Editing Benchmark Emphasizing Modality Consistencycited by 22
  7. 2024Can Editing LLMs Inject Harm?cited by 22
  8. 2025MMKE-Bench: A Multimodal Editing Benchmark for Diverse Visual Knowledgecited by 22
  9. 2024Attribution Analysis Meets Model Editing: Advancing Knowledge Correction in Vision Language Models with VisEditcited by 14
  10. 2024Visual-Oriented Fine-Grained Knowledge Editing for MultiModal Large Language Modelscited by 9
  11. 2024Model Editing for LLMs4Code: How Far are We?cited by 8
  12. 2025MINED: Probing and Updating with Multimodal Time-Sensitive Knowledge for Large Multimodal Modelscited by 7
13 more
  1. 2025OFFSIDE: Benchmarking Unlearning Misinformation in Multimodal Large Language Modelscited by 7
  2. 2025PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Modelscited by 6
  3. 2025E-SAM: Training-Free Segment Every Entity Modelcited by 2
  4. 2025SNS-Bench-VL: Benchmarking Multimodal Large Language Models in Social Networking Servicescited by 2
  5. 2025MemEIC: A Step Toward Continual and Compositional Knowledge Editingcited by 2
  6. 2025Towards Meta-Cognitive Knowledge Editing for Multimodal LLMscited by 1
  7. 2026Generalizable Multimodal Large Language Model Editing via Invariant Trajectory Learningcited by 1
  8. 2025ADS-Edit: A Multimodal Knowledge Editing Dataset for Autonomous Driving Systemscited by 0
  9. 2025Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Modelscited by 0
  10. 2026Uncovering Entity Identity Confusion in Multimodal Knowledge Editingcited by 0
  11. 2026CrossCult-KIBench: A Benchmark for Cross-Cultural Knowledge Insertion in MLLMscited by 0
  12. 2026Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignmentcited by 0
  13. 2026Where a New Concept Must Enter: Entry Point Gates Cross-Task Usability in Unified Multimodal Modelscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024ComprehendEdit: A Comprehensive Dataset and Evaluation Framework for Multimodal Knowledge Editing
  2. 2024UniMEL: A Unified Framework for Multimodal Entity Linking with Large Language Models
  3. 2026Towards Localized and Disentangled Knowledge Editing for Multimodal Large Language Models
  4. 2026SAKE: Self-aware Knowledge Exploitation-Exploration for Grounded Multimodal Named Entity Recognition
  5. 2024Exploring the Implicit Semantic Ability of Multimodal Large Language Models: A Pilot Study on Entity Set Expansion
  6. 2026Beyond Unimodal Shortcuts: MLLMs as Cross-Modal Reasoners for Grounded Named Entity Recognition
  7. 2025KGMEL: Knowledge Graph-Enhanced Multimodal Entity Linking
  8. 2026Multi-Perspective Evidence Synthesis and Reasoning for Unsupervised Multimodal Entity Linking