2025 "hallucination mitigation" Papers
17 papers found
Auditing Meta-Cognitive Hallucinations in Reasoning Large Language Models
Haolang Lu, Yilian Liu, Jingxin Xu et al.
NEURIPS 2025posterarXiv:2505.13143
5
citations
Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent
Yangning Li, Yinghui Li, Xinyu Wang et al.
ICLR 2025posterarXiv:2411.02937
54
citations
DAMO: Decoding by Accumulating Activations Momentum for Mitigating Hallucinations in Vision-Language Models
Kaishen Wang, Hengrui Gu, Meijun Gao et al.
ICLR 2025poster
7
citations
Differential Transformer
Tianzhu Ye, Li Dong, Yuqing Xia et al.
ICLR 2025posterarXiv:2410.05258
ECBench: Can Multi-modal Foundation Models Understand the Egocentric World? A Holistic Embodied Cognition Benchmark
Ronghao Dang, Yuqian Yuan, Wenqi Zhang et al.
CVPR 2025posterarXiv:2501.05031
16
citations
Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval
Sheryl Hsu, Omar Khattab, Chelsea Finn et al.
ICLR 2025posterarXiv:2410.23214
15
citations
Grounding Language with Vision: A Conditional Mutual Information Calibrated Decoding Strategy for Reducing Hallucinations in LVLMs
Hao Fang, Changle Zhou, Jiawei Kong et al.
NEURIPS 2025posterarXiv:2505.19678
6
citations
INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling
Xin Dong, Shichao Dong, Jin Wang et al.
ICCV 2025posterarXiv:2507.05056
3
citations
Intervene-All-Paths: Unified Mitigation of LVLM Hallucinations across Alignment Formats
Jiaye Qian, Ge Zheng, Yuchen Zhu et al.
NEURIPS 2025posterarXiv:2511.17254
2
citations
LIRA: Inferring Segmentation in Large Multi-modal Models with Local Interleaved Region Assistance
Zhang Li, Biao Yang, Qiang Liu et al.
ICCV 2025posterarXiv:2507.06272
1
citations
Mitigating Hallucination in VideoLLMs via Temporal-Aware Activation Engineering
JIANFENG CAI, Jiale Hong, Zongmeng Zhang et al.
NEURIPS 2025oralarXiv:2505.12826
1
citations
Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding
feilong tang, Chengzhi Liu, Zhongxing Xu et al.
CVPR 2025posterarXiv:2505.16652
22
citations
Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
Ce Zhang, Zifu Wan, Zhehan Kan et al.
ICLR 2025posterarXiv:2502.06130
21
citations
Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models
Fushuo Huo, Wenchao Xu, Zhong Zhang et al.
ICLR 2025posterarXiv:2408.02032
61
citations
The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio
Sicong Leng, Yun Xing, Zesen Cheng et al.
NEURIPS 2025posterarXiv:2410.12787
27
citations
Visual Description Grounding Reduces Hallucinations and Boosts Reasoning in LVLMs
Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar et al.
ICLR 2025posterarXiv:2405.15683
15
citations
Why LVLMs Are More Prone to Hallucinations in Longer Responses: The Role of Context
Ge Zheng, Jiaye Qian, Jiajin Tang et al.
ICCV 2025posterarXiv:2510.20229
6
citations