:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Carragher, Peter, Rao, Nikitha, Jha, Abhinand, Raghav, R, Carley, Kathleen M.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence Computation and Language Machine Learning
Accesso online:	https://arxiv.org/abs/2502.14908
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Quantifying Memorization and Parametric Response Rates in Retrieval-Augmented Vision-Language Models
di: Carragher, Peter, et al.
Pubblicazione: (2025)

Unraveling Cross-Modality Knowledge Conflicts in Large Vision-Language Models
di: Zhu, Tinghui, et al.
Pubblicazione: (2024)

Conflict Adaptation in Vision-Language Models
di: Hu, Xiaoyang
Pubblicazione: (2025)

Multimodal LLMs Struggle with Basic Visual Network Analysis: a VNA Benchmark
di: Williams, Evan M., et al.
Pubblicazione: (2024)

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

Malayalam Sign Language Identification using Finetuned YOLOv8 and Computer Vision Techniques
di: K., Abhinand, et al.
Pubblicazione: (2024)

Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models
di: Lovenia, Holy, et al.
Pubblicazione: (2023)

HEED: Density-Weighted Residual Alignment for Hybrid Vision-Language Model Distillation
di: Liang, Yihao, et al.
Pubblicazione: (2026)

Evaluation and Enhancement of Semantic Grounding in Large Vision-Language Models
di: Lu, Jiaying, et al.
Pubblicazione: (2023)

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

AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models
di: Wu, Xiyang, et al.
Pubblicazione: (2024)

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

ESREAL: Exploiting Semantic Reconstruction to Mitigate Hallucinations in Vision-Language Models
di: Kim, Minchan, et al.
Pubblicazione: (2024)

Multi-Object Hallucination in Vision-Language Models
di: Chen, Xuweiyi, et al.
Pubblicazione: (2024)

Insight Over Sight: Exploring the Vision-Knowledge Conflicts in Multimodal LLMs
di: Liu, Xiaoyuan, et al.
Pubblicazione: (2024)

BEAF: Observing BEfore-AFter Changes to Evaluate Hallucination in Vision-language Models
di: Ye-Bin, Moon, et al.
Pubblicazione: (2024)

Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings
di: Agrawal, Aakriti, et al.
Pubblicazione: (2025)

Does Object Grounding Really Reduce Hallucination of Large Vision-Language Models?
di: Geigle, Gregor, et al.
Pubblicazione: (2024)

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models
di: Jing, Liqiang, et al.
Pubblicazione: (2025)

Instruction-Aligned Visual Attention for Mitigating Hallucinations in Large Vision-Language Models
di: Li, Bin, et al.
Pubblicazione: (2025)

From Pixels to Tokens: Revisiting Object Hallucinations in Large Vision-Language Models
di: Shang, Yuying, et al.
Pubblicazione: (2024)

A Survey on Hallucination in Large Vision-Language Models
di: Liu, Hanchao, et al.
Pubblicazione: (2024)

Mitigating Multilingual Hallucination in Large Vision-Language Models
di: Qu, Xiaoye, et al.
Pubblicazione: (2024)

Benchmarking Deflection and Hallucination in Large Vision-Language Models
di: Moratelli, Nicholas, et al.
Pubblicazione: (2026)

ODE: Open-Set Evaluation of Hallucinations in Multimodal Large Language Models
di: Tu, Yahan, et al.
Pubblicazione: (2024)

EmotionHallucer: Evaluating Emotion Hallucinations in Multimodal Large Language Models
di: Xing, Bohao, et al.
Pubblicazione: (2025)

PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model
di: Arif, Kazi Hasan Ibn, et al.
Pubblicazione: (2025)

Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding
di: Wang, Chao, et al.
Pubblicazione: (2025)

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
di: Zhang, Ce, et al.
Pubblicazione: (2025)

Watch Closely: Mitigating Object Hallucinations in Large Vision-Language Models with Disentangled Decoding
di: Ma, Ruiqi, et al.
Pubblicazione: (2025)

ONLY: One-Layer Intervention Sufficiently Mitigates Hallucinations in Large Vision-Language Models
di: Wan, Zifu, et al.
Pubblicazione: (2025)

VEGAS: Mitigating Hallucinations in Large Vision-Language Models via Vision-Encoder Attention Guided Adaptive Steering
di: Wang, Zihu, et al.
Pubblicazione: (2025)

Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Models
di: Wu, Junjie, et al.
Pubblicazione: (2024)

VLMInferSlow: Evaluating the Efficiency Robustness of Large Vision-Language Models as a Service
di: Wang, Xiasi, et al.
Pubblicazione: (2025)

"See the World, Discover Knowledge": A Chinese Factuality Evaluation for Large Vision Language Models
di: Gu, Jihao, et al.
Pubblicazione: (2025)

On the Cultural Anachronism and Temporal Reasoning in Vision Language Models
di: Ranjan, Mukul, et al.
Pubblicazione: (2026)

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
di: Zhou, Yiyang, et al.
Pubblicazione: (2023)

When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise
di: Shin, Philip Wootaek, et al.
Pubblicazione: (2026)

Arbitration Failure, Not Perceptual Blindness: How Vision-Language Models Resolve Visual-Linguistic Conflicts
di: Nooralahzadeh, Farhad, et al.
Pubblicazione: (2026)

HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models
di: Guan, Tianrui, et al.
Pubblicazione: (2023)