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Alleviating Hallucination in Large Vision-Language Models with Active Retrieval Augmentation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-031-20074-8_9openalex-snapshot
A-OKVQA: A Benchmark for Visual Question Answering Using World Knowledge
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1109/cvpr.2017.389openalex-snapshot
Re-ranking Person Re-identification with k-Reciprocal Encoding
inferredcites →https://doi.org/10.1109/cvpr.2019.00686openalex-snapshot
GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering
inferredcites →https://doi.org/10.1109/cvpr52729.2023.00278openalex-snapshot
Smallcap: Lightweight Image Captioning Prompted with Retrieval Augmentation
inferredcites →https://doi.org/10.1145/3539225openalex-snapshot
Retrieval Augmented Convolutional Encoder-decoder Networks for Video Captioning
inferredcites →https://doi.org/10.1162/tacl_a_00605openalex-snapshot
In-Context Retrieval-Augmented Language Models
inferredcites →https://doi.org/10.48550/arxiv.2308.12966openalex-snapshot
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s11263-025-02607-zopenalex-snapshot
Attention Reallocation: Towards Zero-cost and Controllable Hallucination Mitigation of MLLMs
inferred← citeshttps://doi.org/10.1016/j.inffus.2025.103455openalex-snapshot
Knowledge fusion in deep learning-based medical vision-language models: A review
inferred← citeshttps://doi.org/10.1016/j.neucom.2026.132780openalex-snapshot
Multi-scale steering of large vision language models via visual information intervention
inferred← citeshttps://doi.org/10.1109/icassp55912.2026.11460316openalex-snapshot
Attention to Details, Logits to Truth: Visual-Aware Attention and Logits Enhancement to Mitigate Hallucinations in LVLMS
inferred← citeshttps://doi.org/10.1109/icassp55912.2026.11464698openalex-snapshot
VCE: A Zero-Cost Hallucination Mitigation Method of LVLMs via Visual Contrastive Editing
inferred← citeshttps://doi.org/10.1109/iccbdai66607.2025.11388225openalex-snapshot
A Latent Space Intervention Method for Mitigating Hallucinations in Multimodal Large Models
inferred← citeshttps://doi.org/10.1109/icetsis68266.2026.11549183openalex-snapshot
Reducing Hallucinations in Multi-Hop Question Answering Using Wikidata-Based Retrieval-Augmented Generation
inferred← citeshttps://doi.org/10.1109/jcdl67857.2025.00025openalex-snapshot
A Multi-Agent System for Complex Reasoning in Radiology Visual Question Answering
inferred← citeshttps://doi.org/10.1145/3797025openalex-snapshot
Mitigating Multilingual Hallucination in Large Vision-Language Models
inferred← citeshttps://doi.org/10.1145/3829807.3829915openalex-snapshot
From Malfunction to Method: Artistic Strategies for Working with GenAI's Limitations
inferred← citeshttps://doi.org/10.32388/ooam1qopenalex-snapshot
Large Vision-Language Model Alignment and Misalignment: A Survey Through the Lens of Explainability
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