Copertina

KVSmooth: Mitigating Hallucination in Multi-modal Large Language Models through Key-Value Smoothing

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Jiang, Siyu, Chen, Feiyang, Zhang, Xiaojin, He, Kun
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Seeing is Believing? Mitigating OCR Hallucinations in Multimodal Large Language Models
di: He, Zhentao, et al.
Pubblicazione: (2025)

MIHBench: Benchmarking and Mitigating Multi-Image Hallucinations in Multimodal Large Language Models
di: Li, Jiale, et al.
Pubblicazione: (2025)

Mitigating Hallucinations in Large Vision-Language Models via DPO: On-Policy Data Hold the Key
di: Yang, Zhihe, et al.
Pubblicazione: (2025)

Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
di: Lu, Yifan, et al.
Pubblicazione: (2025)

Mitigating Hallucination in Large Vision-Language Models through Aligning Attention Distribution to Information Flow
di: Zhao, Jianfei, et al.
Pubblicazione: (2025)

PruneHal: Reducing Hallucinations in Multi-modal Large Language Models through Adaptive KV Cache Pruning
di: Sun, Fengyuan, et al.
Pubblicazione: (2025)

Mitigating Hallucinations in Large Vision-Language Models via Causal Route Gating
di: Cheng, Zhe, et al.
Pubblicazione: (2026)

Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation
di: Zhu, Xingyu, et al.
Pubblicazione: (2026)

What if...?: Thinking Counterfactual Keywords Helps to Mitigate Hallucination in Large Multi-modal Models
di: Kim, Junho, et al.
Pubblicazione: (2024)

AVCD: Mitigating Hallucinations in Audio-Visual Large Language Models through Contrastive Decoding
di: Jung, Chaeyoung, et al.
Pubblicazione: (2025)

Hallu-PI: Evaluating Hallucination in Multi-modal Large Language Models within Perturbed Inputs
di: Ding, Peng, et al.
Pubblicazione: (2024)

Reflective Instruction Tuning: Mitigating Hallucinations in Large Vision-Language Models
di: Zhang, Jinrui, et al.
Pubblicazione: (2024)

Visual Hallucinations of Multi-modal Large Language Models
di: Huang, Wen, et al.
Pubblicazione: (2024)

Empowering Segmentation Ability to Multi-modal Large Language Models
di: Yang, Yuqi, et al.
Pubblicazione: (2024)

Prefill-Time Intervention for Mitigating Hallucination in Large Vision-Language Models
di: Zhang, Chengsheng, et al.
Pubblicazione: (2026)

Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization
di: Lyu, Xinyu, et al.
Pubblicazione: (2024)

Extracting Visual Facts from Intermediate Layers for Mitigating Hallucinations in Multimodal Large Language Models
di: Zhou, Haoran, et al.
Pubblicazione: (2025)

Improving Multi-modal Large Language Model through Boosting Vision Capabilities
di: Sun, Yanpeng, et al.
Pubblicazione: (2024)

Dynamic Multimodal Activation Steering for Hallucination Mitigation in Large Vision-Language Models
di: Yin, Jianghao, et al.
Pubblicazione: (2026)

Exploring Causes and Mitigation of Hallucinations in Large Vision Language Models
di: Sun, Yaqi, et al.
Pubblicazione: (2025)

Mitigating Modality Prior-Induced Hallucinations in Multimodal Large Language Models via Deciphering Attention Causality
di: Zhou, Guanyu, et al.
Pubblicazione: (2024)

A Unified Hallucination Mitigation Framework for Large Vision-Language Models
di: Chang, Yue, et al.
Pubblicazione: (2024)

VORD: Visual Ordinal Calibration for Mitigating Object Hallucinations in Large Vision-Language Models
di: Neo, Dexter, et al.
Pubblicazione: (2024)

Med-VCD: Mitigating Hallucination for Medical Large Vision Language Models through Visual Contrastive Decoding
di: Mahdavi, Zahra, et al.
Pubblicazione: (2025)

CAI: Caption-Sensitive Attention Intervention for Mitigating Object Hallucination in Large Vision-Language Models
di: Li, Qiming, et al.
Pubblicazione: (2025)

Relaxing Anchor-Frame Dominance for Mitigating Hallucinations in Video Large Language Models
di: Liu, Zijian, et al.
Pubblicazione: (2026)

VERHallu: Evaluating and Mitigating Event Relation Hallucination in Video Large Language Models
di: Zhang, Zefan, et al.
Pubblicazione: (2026)

LISA: A Layer-wise Integration and Suppression Approach for Hallucination Mitigation in Multimodal Large Language Models
di: Guo, Zhihui, et al.
Pubblicazione: (2025)

SAKED: Mitigating Hallucination in Large Vision-Language Models via Stability-Aware Knowledge Enhanced Decoding
di: Li, Zhaoxu, et al.
Pubblicazione: (2026)

Efficient Multi-modal Large Language Models via Progressive Consistency Distillation
di: Wen, Zichen, et al.
Pubblicazione: (2025)

YARD: Y-Architecture Register Decoding for Efficient Hallucination Mitigation in Large Vision-Language Models
di: Chen, Ting, et al.
Pubblicazione: (2026)

SAVER: Mitigating Hallucinations in Large Vision-Language Models via Style-Aware Visual Early Revision
di: Li, Zhaoxu, et al.
Pubblicazione: (2025)

Mitigating Entangled Steering in Large Vision-Language Models for Hallucination Reduction
di: Zhang, Yuanhong, et al.
Pubblicazione: (2026)

Look Carefully: Adaptive Visual Reinforcements in Multimodal Large Language Models for Hallucination Mitigation
di: Zhu, Xingyu, et al.
Pubblicazione: (2026)

Interpreting and Mitigating Hallucination in MLLMs through Multi-agent Debate
di: Lin, Zheng, et al.
Pubblicazione: (2024)

Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via Attention Lens
di: Jiang, Zhangqi, et al.
Pubblicazione: (2024)

DHCP: Detecting Hallucinations by Cross-modal Attention Pattern in Large Vision-Language Models
di: Zhang, Yudong, et al.
Pubblicazione: (2024)

Nullu: Mitigating Object Hallucinations in Large Vision-Language Models via HalluSpace Projection
di: Yang, Le, et al.
Pubblicazione: (2024)

Mitigating Image Captioning Hallucinations in Vision-Language Models
di: Zhao, Fei, et al.
Pubblicazione: (2025)

Diving into Mitigating Hallucinations from a Vision Perspective for Large Vision-Language Models
di: Wang, Weihang, et al.
Pubblicazione: (2025)