Data to 7 Oct 2026

Good News, Everyone! Context driven entity-aware captioning for news images

arXiv 1904.01475 ↗First posted 2 Apr 2019cs.CVcited by 66

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Abstract (arXiv)

Current image captioning systems perform at a merely descriptive level, essentially enumerating the objects in the scene and their relations. Humans, on the contrary, interpret images by integrating several sources of prior knowledge of the world. In this work, we aim to take a step closer to producing captions that offer a plausible interpretation of the scene, by integrating such contextual information into the captioning pipeline. For this we focus on the captioning of images used to illustrate news articles. We propose a novel captioning method that is able to leverage contextual information provided by the text of news articles associated with an image. Our model is able to selectively draw information from the article guided by visual cues, and to dynamically extend the output dictionary to out-of-vocabulary named entities that appear in the context source. Furthermore we introduce `GoodNews', the largest news image captioning dataset in the literature and demonstrate state-of-the-art results.

Key facts. Cited by 66 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Apr 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 11; 2022: 14; 2023: 15; 2024: 15; 2025: 8; 2026: 3.

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2021CLIPScore: A Reference-free Evaluation Metric for Image Captioningcited by 2,388
2021From Show to Tell: A Survey on Deep Learning-based Image Captioningcited by 137
2023Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entitiescited by 112
2021Let there be a clock on the beach: Reducing Object Hallucination in Image Captioningcited by 74
2022Multi-Modal Knowledge Graph Construction and Application: A Surveycited by 74
2021Transparent Human Evaluation for Image Captioningcited by 40
2022Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspectivecited by 40
2022WikiDiverse: A Multimodal Entity Linking Dataset with Diversified Contextual Topics and Entity Typescited by 33
2021Boosting Entity-aware Image Captioning with Multi-modal Knowledge Graphcited by 31
2021Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generationcited by 30
2022Multimodal Knowledge Alignment with Reinforcement Learningcited by 30
2023Multimodality Representation Learning: A Survey on Evolution, Pretraining and Its Applicationscited by 27

38 more

2022Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metricscited by 18
2023A Suite of Generative Tasks for Multi-Level Multimodal Webpage Understandingcited by 18
2021Concadia: Towards Image-Based Text Generation with a Purposecited by 15
2022Visual Named Entity Linking: A New Dataset and A Baselinecited by 15
2021Journalistic Guidelines Aware News Image Captioningcited by 14
2022G^3: Geolocation via Guidebook Groundingcited by 12
2023Visually-Aware Context Modeling for News Image Captioningcited by 12
2021ICECAP: Information Concentrated Entity-aware Image Captioningcited by 11
2022CapOnImage: Context-driven Dense-Captioning on Imagecited by 11
2024Machine-Generated Text Localizationcited by 11
2022Show, Interpret and Tell: Entity-aware Contextualised Image Captioning in Wikipediacited by 10
2022Focus! Relevant and Sufficient Context Selection for News Image Captioningcited by 10
2023Beyond Generic: Enhancing Image Captioning with Real-World Knowledge using Vision-Language Pre-Training Modelcited by 10
2023BIG-C: a Multimodal Multi-Purpose Dataset for Bembacited by 9
2023Dealing with Semantic Underspecification in Multimodal NLPcited by 9
2023WikiWeb2M: A Page-Level Multimodal Wikipedia Datasetcited by 8
2025The Coherence Trap: When MLLM-Crafted Narratives Exploit Manipulated Visual Contextscited by 8
2023"Let's not Quote out of Context": Unified Vision-Language Pretraining for Context Assisted Image Captioningcited by 7
2023DocumentCLIP: Linking Figures and Main Body Text in Reflowed Documentscited by 7
2025Real, Fake, or Manipulated? Detecting Machine-Influenced Textcited by 6
2026The Paradigm Shift: A Comprehensive Survey on Large Vision Language Models for Multimodal Fake News Detectioncited by 6
2022NewsStories: Illustrating articles with visual summariescited by 5
2024Web-Scale Visual Entity Recognition: An LLM-Driven Data Approachcited by 5
2025Beyond Artificial Misalignment: Detecting and Grounding Semantic-Coordinated Multimodal Manipulationscited by 4
2021Show, Write, and Retrieve: Entity-aware Article Generation and Retrievalcited by 3
2022Generating image captions with external encyclopedic knowledgecited by 3
2022Vision and Structured-Language Pretraining for Cross-Modal Food Retrievalcited by 3
2023Explore and Tell: Embodied Visual Captioning in 3D Environmentscited by 3
2024Controllable Contextualized Image Captioning: Directing the Visual Narrative through User-Defined Highlightscited by 3
2025Knowledge Completes the Vision: A Multimodal Entity-aware Retrieval-Augmented Generation Framework for News Image Captioningcited by 3
2023UIT-OpenViIC: A Novel Benchmark for Evaluating Image Captioning in Vietnamesecited by 2
2021Goal-driven text descriptions for imagescited by 1
2023Transform, Contrast and Tell: Coherent Entity-Aware Multi-Image Captioningcited by 1
2024EAMA : Entity-Aware Multimodal Alignment Based Approach for News Image Captioningcited by 1
2024Rule-driven News Captioningcited by 1
2024Detecting Multimodal Situations with Insufficient Context and Abstaining from Baseless Predictionscited by 1
2024A look under the hood of the Interactive Deep Learning Enterprise (No-IDLE)cited by 1
2024Enhancing Journalism with AI: A Study of Contextualized Image Captioning for News Articles using LLMs and LMMscited by 1

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