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Object Hallucination

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Showing 26–50 of 71 papers

TitleStatusHype
Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided DecodingCode1
DAMRO: Dive into the Attention Mechanism of LVLM to Reduce Object Hallucination—0
Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) ModelsCode0
Understanding Multimodal Hallucination with Parameter-Free Representation AlignmentCode0
Multi-Object Hallucination in Vision-Language ModelsCode1
Does Object Grounding Really Reduce Hallucination of Large Vision-Language Models?—0
Do More Details Always Introduce More Hallucinations in LVLM-based Image Captioning?—0
Understanding Sounds, Missing the Questions: The Challenge of Object Hallucination in Large Audio-Language ModelsCode2
Data-augmented phrase-level alignment for mitigating object hallucination—0
RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in Large Vision Language Models—0
RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V TrustworthinessCode11
Think Before You Act: A Two-Stage Framework for Mitigating Gender Bias Towards Vision-Language TasksCode0
ALOHa: A New Measure for Hallucination in Captioning Models—0
Effectiveness Assessment of Recent Large Vision-Language Models—0
HALC: Object Hallucination Reduction via Adaptive Focal-Contrast DecodingCode2
GROUNDHOG: Grounding Large Language Models to Holistic Segmentation—0
Seeing is Believing: Mitigating Hallucination in Large Vision-Language Models via CLIP-Guided DecodingCode1
Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language ModelsCode1
EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language ModelsCode1
Mitigating Object Hallucination in Large Vision-Language Models via Classifier-Free Guidance—0
Instruction Makes a DifferenceCode0
MoE-LLaVA: Mixture of Experts for Large Vision-Language ModelsCode7
Towards Enhanced Image Inpainting: Mitigating Unwanted Object Insertion and Preserving Color ConsistencyCode1
Mitigating Fine-Grained Hallucination by Fine-Tuning Large Vision-Language Models with Caption RewritesCode1
Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive DecodingCode2
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