PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model
Fuente:
arXiv
Saved in:
| Main Authors: | Arif, Kazi Hasan Ibn, Dip, Sajib Acharjee, Hussain, Khizar, Zhang, Lang, Thomas, Chris |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Equitable Skin Disease Prediction Using Transfer Learning and Domain Adaptation
by: Dip, Sajib Acharjee, et al.
Published: (2024)
by: Dip, Sajib Acharjee, et al.
Published: (2024)
PlantMarkerBench: A Multi-Species Benchmark for Evidence-Grounded Plant Marker Reasoning
by: Dip, Sajib Acharjee, et al.
Published: (2026)
by: Dip, Sajib Acharjee, et al.
Published: (2026)
HiRED: Attention-Guided Token Dropping for Efficient Inference of High-Resolution Vision-Language Models
by: Arif, Kazi Hasan Ibn, et al.
Published: (2024)
by: Arif, Kazi Hasan Ibn, et al.
Published: (2024)
Instruction-Aligned Visual Attention for Mitigating Hallucinations in Large Vision-Language Models
by: Li, Bin, et al.
Published: (2025)
by: Li, Bin, et al.
Published: (2025)
Mitigating Hallucination in Large Vision-Language Models via Adaptive Attention Calibration
by: Fazli, Mehrdad, et al.
Published: (2025)
by: Fazli, Mehrdad, et al.
Published: (2025)
Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
by: Lu, Yifan, et al.
Published: (2025)
by: Lu, Yifan, et al.
Published: (2025)
Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding
by: Wang, Xintong, et al.
Published: (2024)
by: Wang, Xintong, et al.
Published: (2024)
VEGAS: Mitigating Hallucinations in Large Vision-Language Models via Vision-Encoder Attention Guided Adaptive Steering
by: Wang, Zihu, et al.
Published: (2025)
by: Wang, Zihu, et al.
Published: (2025)
AI for Biomedicine in the Era of Large Language Models
by: Bi, Zhenyu, et al.
Published: (2024)
by: Bi, Zhenyu, et al.
Published: (2024)
Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention
by: An, Wenbin, et al.
Published: (2024)
by: An, Wenbin, et al.
Published: (2024)
Mitigating Multilingual Hallucination in Large Vision-Language Models
by: Qu, Xiaoye, et al.
Published: (2024)
by: Qu, Xiaoye, et al.
Published: (2024)
A Unified Hallucination Mitigation Framework for Large Vision-Language Models
by: Chang, Yue, et al.
Published: (2024)
by: Chang, Yue, et al.
Published: (2024)
Diving into Mitigating Hallucinations from a Vision Perspective for Large Vision-Language Models
by: Wang, Weihang, et al.
Published: (2025)
by: Wang, Weihang, et al.
Published: (2025)
LLM4Cell: A Survey of Large Language and Agentic Models for Single-Cell Biology
by: Dip, Sajib Acharjee, et al.
Published: (2025)
by: Dip, Sajib Acharjee, et al.
Published: (2025)
From Pixels to Tokens: Revisiting Object Hallucinations in Large Vision-Language Models
by: Shang, Yuying, et al.
Published: (2024)
by: Shang, Yuying, et al.
Published: (2024)
Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models
by: Chen, Xinlong, et al.
Published: (2025)
by: Chen, Xinlong, et al.
Published: (2025)
CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention
by: Ye, Zekai, et al.
Published: (2025)
by: Ye, Zekai, et al.
Published: (2025)
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
by: Zhou, Yiyang, et al.
Published: (2023)
by: Zhou, Yiyang, et al.
Published: (2023)
Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings
by: Agrawal, Aakriti, et al.
Published: (2025)
by: Agrawal, Aakriti, et al.
Published: (2025)
Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding
by: Wang, Chao, et al.
Published: (2025)
by: Wang, Chao, et al.
Published: (2025)
Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
by: Zhang, Ce, et al.
Published: (2025)
by: Zhang, Ce, et al.
Published: (2025)
Watch Closely: Mitigating Object Hallucinations in Large Vision-Language Models with Disentangled Decoding
by: Ma, Ruiqi, et al.
Published: (2025)
by: Ma, Ruiqi, et al.
Published: (2025)
ONLY: One-Layer Intervention Sufficiently Mitigates Hallucinations in Large Vision-Language Models
by: Wan, Zifu, et al.
Published: (2025)
by: Wan, Zifu, et al.
Published: (2025)
Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models
by: Zhong, Weihong, et al.
Published: (2024)
by: Zhong, Weihong, et al.
Published: (2024)
On Epistemic Uncertainty of Visual Tokens for Object Hallucinations in Large Vision-Language Models
by: Seo, Hoigi, et al.
Published: (2025)
by: Seo, Hoigi, et al.
Published: (2025)
PARALLAX: Separating Genuine Hallucination Detection from Benchmark Construction Artifacts
by: Hussain, Khizar, et al.
Published: (2026)
by: Hussain, Khizar, et al.
Published: (2026)
Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding
by: Min, Kyungmin, et al.
Published: (2024)
by: Min, Kyungmin, et al.
Published: (2024)
Delve into Visual Contrastive Decoding for Hallucination Mitigation of Large Vision-Language Models
by: Lee, Yi-Lun, et al.
Published: (2024)
by: Lee, Yi-Lun, et al.
Published: (2024)
ESREAL: Exploiting Semantic Reconstruction to Mitigate Hallucinations in Vision-Language Models
by: Kim, Minchan, et al.
Published: (2024)
by: Kim, Minchan, et al.
Published: (2024)
Mitigating Hallucinations in Large Vision-Language Models (LVLMs) via Language-Contrastive Decoding (LCD)
by: Manevich, Avshalom, et al.
Published: (2024)
by: Manevich, Avshalom, et al.
Published: (2024)
Efficient Contrastive Decoding with Probabilistic Hallucination Detection - Mitigating Hallucinations in Large Vision Language Models -
by: Fieback, Laura, et al.
Published: (2025)
by: Fieback, Laura, et al.
Published: (2025)
Mitigating Object Hallucination via Concentric Causal Attention
by: Xing, Yun, et al.
Published: (2024)
by: Xing, Yun, et al.
Published: (2024)
ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models
by: Chen, Junzhe, et al.
Published: (2024)
by: Chen, Junzhe, et al.
Published: (2024)
Black-Box Visual Prompt Engineering for Mitigating Object Hallucination in Large Vision Language Models
by: Woo, Sangmin, et al.
Published: (2025)
by: Woo, Sangmin, et al.
Published: (2025)
Mitigating Hallucinations in Large Vision-Language Models via Entity-Centric Multimodal Preference Optimization
by: Wu, Jiulong, et al.
Published: (2025)
by: Wu, Jiulong, et al.
Published: (2025)
PathoLM: Identifying pathogenicity from the DNA sequence through the Genome Foundation Model
by: Dip, Sajib Acharjee, et al.
Published: (2024)
by: Dip, Sajib Acharjee, et al.
Published: (2024)
NoLan: Mitigating Object Hallucinations in Large Vision-Language Models via Dynamic Suppression of Language Priors
by: Ren, Lingfeng, et al.
Published: (2026)
by: Ren, Lingfeng, et al.
Published: (2026)
First Logit Boosting: Visual Grounding Method to Mitigate Object Hallucination in Large Vision-Language Models
by: Ha, Jiwoo, et al.
Published: (2026)
by: Ha, Jiwoo, et al.
Published: (2026)
Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance
by: Zhao, Linxi, et al.
Published: (2024)
by: Zhao, Linxi, et al.
Published: (2024)
Vision-centric Token Compression in Large Language Model
by: Xing, Ling, et al.
Published: (2025)
by: Xing, Ling, et al.
Published: (2025)
Similar Items
-
Equitable Skin Disease Prediction Using Transfer Learning and Domain Adaptation
by: Dip, Sajib Acharjee, et al.
Published: (2024) -
PlantMarkerBench: A Multi-Species Benchmark for Evidence-Grounded Plant Marker Reasoning
by: Dip, Sajib Acharjee, et al.
Published: (2026) -
HiRED: Attention-Guided Token Dropping for Efficient Inference of High-Resolution Vision-Language Models
by: Arif, Kazi Hasan Ibn, et al.
Published: (2024) -
Instruction-Aligned Visual Attention for Mitigating Hallucinations in Large Vision-Language Models
by: Li, Bin, et al.
Published: (2025) -
Mitigating Hallucination in Large Vision-Language Models via Adaptive Attention Calibration
by: Fazli, Mehrdad, et al.
Published: (2025)