GroundCount: Grounding Vision-Language Models with Object Detection for Mitigating Counting Hallucinations
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Boyuan, Shao, Minghao, Garg, Siddharth, Karri, Ramesh, Shafique, Muhammad |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
Causally-Grounded Dual-Path Attention Intervention for Object Hallucination Mitigation in LVLMs
by: Yu, Liu, et al.
Published: (2025)
by: Yu, Liu, et al.
Published: (2025)
Kestrel: Grounding Self-Refinement for LVLM Hallucination Mitigation
by: Mao, Jiawei, et al.
Published: (2026)
by: Mao, Jiawei, et al.
Published: (2026)
Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) Models
by: Liu, Yufang, et al.
Published: (2024)
by: Liu, Yufang, et al.
Published: (2024)
LVLM-COUNT: Enhancing the Counting Ability of Large Vision-Language Models
by: Qharabagh, Muhammad Fetrat, et al.
Published: (2024)
by: Qharabagh, Muhammad Fetrat, et al.
Published: (2024)
CounterCount: A Diagnostic Framework for Counting Bias in Vision Language Models
by: Alzahrani, Reem, et al.
Published: (2026)
by: Alzahrani, Reem, et al.
Published: (2026)
Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration
by: Zhu, Younan, et al.
Published: (2025)
by: Zhu, Younan, et al.
Published: (2025)
On the Application of Efficient Neural Mapping to Real-Time Indoor Localisation for Unmanned Ground Vehicles
by: Holder, Christopher J., et al.
Published: (2022)
by: Holder, Christopher J., et al.
Published: (2022)
Understanding Counting Mechanisms in Large Language and Vision-Language Models
by: Hasani, Hosein, et al.
Published: (2025)
by: Hasani, Hosein, et al.
Published: (2025)
Your Vision-Language Model Can't Even Count to 20: Exposing the Failures of VLMs in Compositional Counting
by: Guo, Xuyang, et al.
Published: (2025)
by: Guo, Xuyang, et al.
Published: (2025)
Global Context or Local Detail? Adaptive Visual Grounding for Hallucination Mitigation
by: Jiang, Yubo, et al.
Published: (2026)
by: Jiang, Yubo, et al.
Published: (2026)
Seeing It or Not? Interpretable Vision-aware Latent Steering to Mitigate Object Hallucinations
by: Chen, Boxu, et al.
Published: (2025)
by: Chen, Boxu, et al.
Published: (2025)
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)
Dynamic Multimodal Activation Steering for Hallucination Mitigation in Large Vision-Language Models
by: Yin, Jianghao, et al.
Published: (2026)
by: Yin, Jianghao, et al.
Published: (2026)
CAPTURe: Evaluating Spatial Reasoning in Vision Language Models via Occluded Object Counting
by: Pothiraj, Atin, et al.
Published: (2025)
by: Pothiraj, Atin, et al.
Published: (2025)
PAS : Prelim Attention Score for Detecting Object Hallucinations in Large Vision--Language Models
by: Hoang-Xuan, Nhat, et al.
Published: (2025)
by: Hoang-Xuan, Nhat, et al.
Published: (2025)
VIB-Probe: Detecting and Mitigating Hallucinations in Vision-Language Models via Variational Information Bottleneck
by: Zhang, Feiran, et al.
Published: (2026)
by: Zhang, Feiran, et al.
Published: (2026)
Multi-Object Hallucination in Vision-Language Models
by: Chen, Xuweiyi, et al.
Published: (2024)
by: Chen, Xuweiyi, et al.
Published: (2024)
Open-World Object Counting in Videos
by: Amini-Naieni, Niki, et al.
Published: (2025)
by: Amini-Naieni, Niki, et al.
Published: (2025)
Mitigating Object Hallucinations in Vision-Language Models through Region-Aware Attention Recalibration
by: Xu, Yuanzhi, et al.
Published: (2026)
by: Xu, Yuanzhi, et al.
Published: (2026)
Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models
by: Lee, Jihoon, et al.
Published: (2025)
by: Lee, Jihoon, et al.
Published: (2025)
Prefill-Time Intervention for Mitigating Hallucination in Large Vision-Language Models
by: Zhang, Chengsheng, et al.
Published: (2026)
by: Zhang, Chengsheng, et al.
Published: (2026)
Mitigating Entangled Steering in Large Vision-Language Models for Hallucination Reduction
by: Zhang, Yuanhong, et al.
Published: (2026)
by: Zhang, Yuanhong, et al.
Published: (2026)
Counting Circuits: Mechanistic Interpretability of Visual Reasoning in Large Vision-Language Models
by: Che, Liwei, et al.
Published: (2026)
by: Che, Liwei, et al.
Published: (2026)
DO-Bench: An Attributable Benchmark for Diagnosing Object Hallucination in Vision-Language Models
by: Wang, JiYang, et al.
Published: (2026)
by: Wang, JiYang, et al.
Published: (2026)
Curriculum for Crowd Counting -- Is it Worthy?
by: Khan, Muhammad Asif, et al.
Published: (2024)
by: Khan, Muhammad Asif, 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)
INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling
by: Dong, Xin, et al.
Published: (2025)
by: Dong, Xin, et al.
Published: (2025)
Mitigating Multilingual Hallucination in Large Vision-Language Models
by: Qu, Xiaoye, et al.
Published: (2024)
by: Qu, Xiaoye, et al.
Published: (2024)
CountFormer: A Transformer Framework for Learning Visual Repetition and Structure in Class-Agnostic Object Counting
by: Hossain, Md Tanvir, et al.
Published: (2025)
by: Hossain, Md Tanvir, et al.
Published: (2025)
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)
When Text Hijacks Vision: Benchmarking and Mitigating Text Overlay-Induced Hallucination in Vision Language Models
by: Yakun, Cui, et al.
Published: (2026)
by: Yakun, Cui, et al.
Published: (2026)
Do Not Leave a Gap: Hallucination-Free Object Concealment in Vision-Language Models
by: Guesmi, Amira, et al.
Published: (2026)
by: Guesmi, Amira, et al.
Published: (2026)
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)
EAGLE: Enhanced Visual Grounding Minimizes Hallucinations in Instructional Multimodal Models
by: Villa, Andrés, et al.
Published: (2025)
by: Villa, Andrés, et al.
Published: (2025)
SDCD: Structure-Disrupted Contrastive Decoding for Mitigating Hallucinations in Large Vision-Language Models
by: Xia, Yuxuan, et al.
Published: (2026)
by: Xia, Yuxuan, et al.
Published: (2026)
MedHEval: Benchmarking Hallucinations and Mitigation Strategies in Medical Large Vision-Language Models
by: Chang, Aofei, et al.
Published: (2025)
by: Chang, Aofei, et al.
Published: (2025)
MAP: Mitigating Hallucinations in Large Vision-Language Models with Map-Level Attention Processing
by: Li, Chenxi, et al.
Published: (2025)
by: Li, Chenxi, et al.
Published: (2025)
Physically Grounded Vision-Language Models for Robotic Manipulation
by: Gao, Jensen, et al.
Published: (2023)
by: Gao, Jensen, et al.
Published: (2023)
Similar Items
-
First Logit Boosting: Visual Grounding Method to Mitigate Object Hallucination in Large Vision-Language Models
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) -
Causally-Grounded Dual-Path Attention Intervention for Object Hallucination Mitigation in LVLMs
by: Yu, Liu, et al.
Published: (2025) -
Kestrel: Grounding Self-Refinement for LVLM Hallucination Mitigation
by: Mao, Jiawei, et al.
Published: (2026) -
Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) Models
by: Liu, Yufang, et al.
Published: (2024)