Guardado en:
| Autores principales: | Zhong, Li'an, He, Ziqiang, Zheng, Jibin, Li, Jin, Wang, Z. Jane, Kang, Xiangui |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2603.04908 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
AdvAD: Exploring Non-Parametric Diffusion for Imperceptible Adversarial Attacks
por: Li, Jin, et al.
Publicado: (2025)
por: Li, Jin, et al.
Publicado: (2025)
Cross-Modal Attention Calibration for LVLM Hallucination Mitigation
por: Li, Jiaming, et al.
Publicado: (2025)
por: Li, Jiaming, et al.
Publicado: (2025)
DAMRO: Dive into the Attention Mechanism of LVLM to Reduce Object Hallucination
por: Gong, Xuan, et al.
Publicado: (2024)
por: Gong, Xuan, et al.
Publicado: (2024)
AFTER: Mitigating the Object Hallucination of LVLM via Adaptive Factual-Guided Activation Editing
por: Wang, Tianbo, et al.
Publicado: (2026)
por: Wang, Tianbo, et al.
Publicado: (2026)
ACT Now: Preempting LVLM Hallucinations via Adaptive Context Integration
por: Yan, Bei, et al.
Publicado: (2026)
por: Yan, Bei, et al.
Publicado: (2026)
AdaCluster: Adaptive Query-Key Clustering for Sparse Attention in Video Generation
por: Tan, Haoyue, et al.
Publicado: (2026)
por: Tan, Haoyue, et al.
Publicado: (2026)
Kestrel: Grounding Self-Refinement for LVLM Hallucination Mitigation
por: Mao, Jiawei, et al.
Publicado: (2026)
por: Mao, Jiawei, et al.
Publicado: (2026)
Fighting Hallucinations with Counterfactuals: Diffusion-Guided Perturbations for LVLM Hallucination Suppression
por: Dastmalchi, Hamidreza, et al.
Publicado: (2026)
por: Dastmalchi, Hamidreza, et al.
Publicado: (2026)
Adversarial Orthogonal Disentanglement for LVLM Hallucination Mitigation
por: Cheng, Ruoxi, et al.
Publicado: (2026)
por: Cheng, Ruoxi, et al.
Publicado: (2026)
PGD-Imp: Rethinking and Unleashing Potential of Classic PGD with Dual Strategies for Imperceptible Adversarial Attacks
por: Li, Jin, et al.
Publicado: (2024)
por: Li, Jin, et al.
Publicado: (2024)
Intervene-All-Paths: Unified Mitigation of LVLM Hallucinations across Alignment Formats
por: Qian, Jiaye, et al.
Publicado: (2025)
por: Qian, Jiaye, et al.
Publicado: (2025)
Paying More Attention to Image: A Training-Free Method for Alleviating Hallucination in LVLMs
por: Liu, Shi, et al.
Publicado: (2024)
por: Liu, Shi, et al.
Publicado: (2024)
GM-DF: Generalized Multi-Scenario Deepfake Detection
por: Lai, Yingxin, et al.
Publicado: (2024)
por: Lai, Yingxin, et al.
Publicado: (2024)
Antidote: A Unified Framework for Mitigating LVLM Hallucinations in Counterfactual Presupposition and Object Perception
por: Wu, Yuanchen, et al.
Publicado: (2025)
por: Wu, Yuanchen, et al.
Publicado: (2025)
Fooling the LVLM Judges: Visual Biases in LVLM-Based Evaluation
por: Hwang, Yerin, et al.
Publicado: (2025)
por: Hwang, Yerin, et al.
Publicado: (2025)
Generalized Face Forgery Detection via Adaptive Learning for Pre-trained Vision Transformer
por: Luo, Anwei, et al.
Publicado: (2023)
por: Luo, Anwei, et al.
Publicado: (2023)
SHIELD: Suppressing Hallucinations In LVLM Encoders via Bias and Vulnerability Defense
por: Huang, Yiyang, et al.
Publicado: (2025)
por: Huang, Yiyang, et al.
Publicado: (2025)
Dual Frequency Branch Framework with Reconstructed Sliding Windows Attention for AI-Generated Image Detection
por: Yan, Jiazhen, et al.
Publicado: (2025)
por: Yan, Jiazhen, et al.
Publicado: (2025)
AdaSpark: Adaptive Sparsity for Efficient Long-Video Understanding
por: Li, Handong, et al.
Publicado: (2026)
por: Li, Handong, et al.
Publicado: (2026)
Beyond the Global Scores: Fine-Grained Token Grounding as a Robust Detector of LVLM Hallucinations
por: Nguyen, Tuan Dung, et al.
Publicado: (2026)
por: Nguyen, Tuan Dung, et al.
Publicado: (2026)
LAVID: An Agentic LVLM Framework for Diffusion-Generated Video Detection
por: Liu, Qingyuan, et al.
Publicado: (2025)
por: Liu, Qingyuan, et al.
Publicado: (2025)
Scalpel: Fine-Grained Alignment of Attention Activation Manifolds via Mixture Gaussian Bridges to Mitigate Multimodal Hallucination
por: Shi, Ziqiang, et al.
Publicado: (2026)
por: Shi, Ziqiang, et al.
Publicado: (2026)
AdaEraser: Training-Free Object Removal via Adaptive Attention Suppression
por: Liu, Dingming
Publicado: (2026)
por: Liu, Dingming
Publicado: (2026)
Security Tensors as a Cross-Modal Bridge: Extending Text-Aligned Safety to Vision in LVLM
por: Li, Shen, et al.
Publicado: (2025)
por: Li, Shen, et al.
Publicado: (2025)
Seeing Clearly by Layer Two: Enhancing Attention Heads to Alleviate Hallucination in LVLMs
por: Zhang, Xiaofeng, et al.
Publicado: (2024)
por: Zhang, Xiaofeng, et al.
Publicado: (2024)
$L_p$-norm Distortion-Efficient Adversarial Attack
por: Zhou, Chao, et al.
Publicado: (2024)
por: Zhou, Chao, et al.
Publicado: (2024)
Do More Details Always Introduce More Hallucinations in LVLM-based Image Captioning?
por: Feng, Mingqian, et al.
Publicado: (2024)
por: Feng, Mingqian, et al.
Publicado: (2024)
LVLM-Composer's Explicit Planning for Image Generation
por: Ramsey, Spencer, et al.
Publicado: (2025)
por: Ramsey, Spencer, et al.
Publicado: (2025)
ASAP: Attention-Shift-Aware Pruning for Efficient LVLM Inference
por: Pathak, Surendra, et al.
Publicado: (2026)
por: Pathak, Surendra, et al.
Publicado: (2026)
Spotlight and Shadow: Attention-Guided Dual-Anchor Introspective Decoding for MLLM Hallucination Mitigation
por: Wu, Yebo, et al.
Publicado: (2026)
por: Wu, Yebo, et al.
Publicado: (2026)
Scaling Exposes the Trigger: Input-Level Backdoor Detection in Text-to-Image Diffusion Models via Cross-Attention Scaling
por: Li, Zida, et al.
Publicado: (2026)
por: Li, Zida, et al.
Publicado: (2026)
ViT-AdaLA: Adapting Vision Transformers with Linear Attention
por: Li, Yifan, et al.
Publicado: (2026)
por: Li, Yifan, et al.
Publicado: (2026)
MaskCD: Mitigating LVLM Hallucinations by Image Head Masked Contrastive Decoding
por: Deng, Jingyuan, et al.
Publicado: (2025)
por: Deng, Jingyuan, et al.
Publicado: (2025)
AdaGen: Learning Adaptive Policy for Image Synthesis
por: Ni, Zanlin, et al.
Publicado: (2026)
por: Ni, Zanlin, et al.
Publicado: (2026)
Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models
por: Huo, Fushuo, et al.
Publicado: (2024)
por: Huo, Fushuo, et al.
Publicado: (2024)
AdaLog: Post-Training Quantization for Vision Transformers with Adaptive Logarithm Quantizer
por: Wu, Zhuguanyu, et al.
Publicado: (2024)
por: Wu, Zhuguanyu, et al.
Publicado: (2024)
Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization
por: Lyu, Xinyu, et al.
Publicado: (2024)
por: Lyu, Xinyu, et al.
Publicado: (2024)
AdaFlow: Efficient Long Video Editing via Adaptive Attention Slimming And Keyframe Selection
por: Zhang, Shuheng, et al.
Publicado: (2025)
por: Zhang, Shuheng, et al.
Publicado: (2025)
PA-Attack: Guiding Gray-Box Attacks on LVLM Vision Encoders with Prototypes and Attention
por: Mei, Hefei, et al.
Publicado: (2026)
por: Mei, Hefei, et al.
Publicado: (2026)
AdaEdit: Adaptive Temporal and Channel Modulation for Flow-Based Image Editing
por: Li, Guandong, et al.
Publicado: (2026)
por: Li, Guandong, et al.
Publicado: (2026)
Ejemplares similares
-
AdvAD: Exploring Non-Parametric Diffusion for Imperceptible Adversarial Attacks
por: Li, Jin, et al.
Publicado: (2025) -
Cross-Modal Attention Calibration for LVLM Hallucination Mitigation
por: Li, Jiaming, et al.
Publicado: (2025) -
DAMRO: Dive into the Attention Mechanism of LVLM to Reduce Object Hallucination
por: Gong, Xuan, et al.
Publicado: (2024) -
AFTER: Mitigating the Object Hallucination of LVLM via Adaptive Factual-Guided Activation Editing
por: Wang, Tianbo, et al.
Publicado: (2026) -
ACT Now: Preempting LVLM Hallucinations via Adaptive Context Integration
por: Yan, Bei, et al.
Publicado: (2026)