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Object Hallucination

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Showing 51–71 of 71 papers

TitleStatusHype
KNVQA: A Benchmark for evaluation knowledge-based VQA—0
Data-augmented phrase-level alignment for mitigating object hallucination—0
CutPaste&Find: Efficient Multimodal Hallucination Detector with Visual-aid Knowledge Base—0
Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models—0
OmniPaint: Mastering Object-Oriented Editing via Disentangled Insertion-Removal Inpainting—0
Poison as Cure: Visual Noise for Mitigating Object Hallucinations in LVMs—0
Reducing Object Hallucination in Large Audio-Language Models via Audio-Aware Decoding—0
Relational Graph Learning for Grounded Video Description Generation—0
ALOHa: A New Measure for Hallucination in Captioning Models—0
Vision-Encoders (Already) Know What They See: Mitigating Object Hallucination via Simple Fine-Grained CLIPScoreCode0
Instruction Makes a DifferenceCode0
Explain and Improve: LRP-Inference Fine-Tuning for Image Captioning ModelsCode0
Plausible May Not Be Faithful: Probing Object Hallucination in Vision-Language Pre-trainingCode0
SECOND: Mitigating Perceptual Hallucination in Vision-Language Models via Selective and Contrastive DecodingCode0
Unified Triplet-Level Hallucination Evaluation for Large Vision-Language ModelsCode0
HALLUCINOGEN: A Benchmark for Evaluating Object Hallucination in Large Visual-Language ModelsCode0
Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language ModelsCode0
Think Before You Act: A Two-Stage Framework for Mitigating Gender Bias Towards Vision-Language TasksCode0
Understanding Multimodal Hallucination with Parameter-Free Representation AlignmentCode0
Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) ModelsCode0
Object Hallucination in Image CaptioningCode0
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