ODE: Open-Set Evaluation of Hallucinations in Multimodal Large Language Models
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Tu, Yahan, Hu, Rui, Sang, Jitao |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Prescribing the Right Remedy: Mitigating Hallucinations in Large Vision-Language Models via Targeted Instruction Tuning
par: Hu, Rui, et autres
Publié: (2024)
par: Hu, Rui, et autres
Publié: (2024)
EmotionHallucer: Evaluating Emotion Hallucinations in Multimodal Large Language Models
par: Xing, Bohao, et autres
Publié: (2025)
par: Xing, Bohao, et autres
Publié: (2025)
VaLiD: Mitigating the Hallucination of Large Vision Language Models by Visual Layer Fusion Contrastive Decoding
par: Wang, Jiaqi, et autres
Publié: (2024)
par: Wang, Jiaqi, et autres
Publié: (2024)
Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images
par: You, Liangliang, et autres
Publié: (2025)
par: You, Liangliang, et autres
Publié: (2025)
AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation
par: Wang, Junyang, et autres
Publié: (2023)
par: Wang, Junyang, et autres
Publié: (2023)
Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
par: Lu, Yifan, et autres
Publié: (2025)
par: Lu, Yifan, et autres
Publié: (2025)
Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models
par: Zheng, Kening, et autres
Publié: (2024)
par: Zheng, Kening, et autres
Publié: (2024)
AIGCs Confuse AI Too: Investigating and Explaining Synthetic Image-induced Hallucinations in Large Vision-Language Models
par: Gao, Yifei, et autres
Publié: (2024)
par: Gao, Yifei, et autres
Publié: (2024)
EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models
par: Xing, Shangyu, et autres
Publié: (2024)
par: Xing, Shangyu, et autres
Publié: (2024)
Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models
par: Zhong, Weihong, et autres
Publié: (2024)
par: Zhong, Weihong, et autres
Publié: (2024)
Debiased Prompt Tuning in Vision-Language Model without Annotations
par: Jiang, Chaoquan, et autres
Publié: (2025)
par: Jiang, Chaoquan, et autres
Publié: (2025)
Watch Closely: Mitigating Object Hallucinations in Large Vision-Language Models with Disentangled Decoding
par: Ma, Ruiqi, et autres
Publié: (2025)
par: Ma, Ruiqi, et autres
Publié: (2025)
Mask What Matters: Mitigating Object Hallucinations in Multimodal Large Language Models with Object-Aligned Visual Contrastive Decoding
par: Chen, Boqi, et autres
Publié: (2026)
par: Chen, Boqi, et autres
Publié: (2026)
Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization
par: Fu, Yuhan, et autres
Publié: (2024)
par: Fu, Yuhan, et autres
Publié: (2024)
Woodpecker: Hallucination Correction for Multimodal Large Language Models
par: Yin, Shukang, et autres
Publié: (2023)
par: Yin, Shukang, et autres
Publié: (2023)
HulluEdit: Single-Pass Evidence-Consistent Subspace Editing for Mitigating Hallucinations in Large Vision-Language Models
par: Lin, Yangguang, et autres
Publié: (2026)
par: Lin, Yangguang, et autres
Publié: (2026)
Evaluating Multimodal Large Language Models on Vertically Written Japanese Text
par: Sasagawa, Keito, et autres
Publié: (2025)
par: Sasagawa, Keito, et autres
Publié: (2025)
Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization
par: Pi, Renjie, et autres
Publié: (2024)
par: Pi, Renjie, et autres
Publié: (2024)
Evaluating Large Language Models on Multimodal Chemistry Olympiad Exams
par: Cui, Yiming, et autres
Publié: (2025)
par: Cui, Yiming, et autres
Publié: (2025)
A Unified Hallucination Mitigation Framework for Large Vision-Language Models
par: Chang, Yue, et autres
Publié: (2024)
par: Chang, Yue, et autres
Publié: (2024)
AlignMMBench: Evaluating Chinese Multimodal Alignment in Large Vision-Language Models
par: Wu, Yuhang, et autres
Publié: (2024)
par: Wu, Yuhang, et autres
Publié: (2024)
Focus Matters: Phase-Aware Suppression for Hallucination in Vision-Language Models
par: Kim, Sohyeon, et autres
Publié: (2026)
par: Kim, Sohyeon, et autres
Publié: (2026)
ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models
par: Chen, Junzhe, et autres
Publié: (2024)
par: Chen, Junzhe, et autres
Publié: (2024)
Does Object Grounding Really Reduce Hallucination of Large Vision-Language Models?
par: Geigle, Gregor, et autres
Publié: (2024)
par: Geigle, Gregor, et autres
Publié: (2024)
From Pixels to Tokens: Revisiting Object Hallucinations in Large Vision-Language Models
par: Shang, Yuying, et autres
Publié: (2024)
par: Shang, Yuying, et autres
Publié: (2024)
Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings
par: Agrawal, Aakriti, et autres
Publié: (2025)
par: Agrawal, Aakriti, et autres
Publié: (2025)
A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models
par: Jing, Liqiang, et autres
Publié: (2025)
par: Jing, Liqiang, et autres
Publié: (2025)
Instruction-Aligned Visual Attention for Mitigating Hallucinations in Large Vision-Language Models
par: Li, Bin, et autres
Publié: (2025)
par: Li, Bin, et autres
Publié: (2025)
Mitigating Hallucinations in Large Vision-Language Models via Entity-Centric Multimodal Preference Optimization
par: Wu, Jiulong, et autres
Publié: (2025)
par: Wu, Jiulong, et autres
Publié: (2025)
LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models
par: Zhang, Kaichen, et autres
Publié: (2024)
par: Zhang, Kaichen, et autres
Publié: (2024)
ChartHal: A Fine-grained Framework Evaluating Hallucination of Large Vision Language Models in Chart Understanding
par: Wang, Xingqi, et autres
Publié: (2025)
par: Wang, Xingqi, et autres
Publié: (2025)
Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models
par: Lovenia, Holy, et autres
Publié: (2023)
par: Lovenia, Holy, et autres
Publié: (2023)
PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model
par: Arif, Kazi Hasan Ibn, et autres
Publié: (2025)
par: Arif, Kazi Hasan Ibn, et autres
Publié: (2025)
Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding
par: Wang, Chao, et autres
Publié: (2025)
par: Wang, Chao, et autres
Publié: (2025)
Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
par: Zhang, Ce, et autres
Publié: (2025)
par: Zhang, Ce, et autres
Publié: (2025)
Diving into Mitigating Hallucinations from a Vision Perspective for Large Vision-Language Models
par: Wang, Weihang, et autres
Publié: (2025)
par: Wang, Weihang, et autres
Publié: (2025)
ONLY: One-Layer Intervention Sufficiently Mitigates Hallucinations in Large Vision-Language Models
par: Wan, Zifu, et autres
Publié: (2025)
par: Wan, Zifu, et autres
Publié: (2025)
A Survey on Evaluation of Multimodal Large Language Models
par: Huang, Jiaxing, et autres
Publié: (2024)
par: Huang, Jiaxing, et autres
Publié: (2024)
HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models
par: Guan, Tianrui, et autres
Publié: (2023)
par: Guan, Tianrui, et autres
Publié: (2023)
OpenOmni: Advancing Open-Source Omnimodal Large Language Models with Progressive Multimodal Alignment and Real-Time Self-Aware Emotional Speech Synthesis
par: Luo, Run, et autres
Publié: (2025)
par: Luo, Run, et autres
Publié: (2025)
Documents similaires
-
Prescribing the Right Remedy: Mitigating Hallucinations in Large Vision-Language Models via Targeted Instruction Tuning
par: Hu, Rui, et autres
Publié: (2024) -
EmotionHallucer: Evaluating Emotion Hallucinations in Multimodal Large Language Models
par: Xing, Bohao, et autres
Publié: (2025) -
VaLiD: Mitigating the Hallucination of Large Vision Language Models by Visual Layer Fusion Contrastive Decoding
par: Wang, Jiaqi, et autres
Publié: (2024) -
Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images
par: You, Liangliang, et autres
Publié: (2025) -
AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation
par: Wang, Junyang, et autres
Publié: (2023)