Papers
LLM-Check: Investigating Detection of Hallucinations in Large Language Models
Gaurang Sriramanan, Siddhant Bharti, Vinu Sankar Sadasivan et al.
Reflective Instruction Tuning: Mitigating Hallucinations in Large Vision-Language Models
Jinrui Zhang, Teng Wang, Haigang Zhang et al.
Mitigating Hallucinations of Large Language Models in Medical Information Extraction via Contrastive Decoding
Derong Xu, Ziheng Zhang, Zhihong Zhu et al.
Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding
Xintong Wang, Jingheng Pan, Liang Ding et al.
Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization
Xinyu Lyu, Beitao Chen, Lianli Gao et al.
Detecting and Preventing Hallucinations in Large Vision Language Models
Anisha Gunjal, Jihan Yin, Erhan Bas
ANAH: Analytical Annotation of Hallucinations in Large Language Models
Ziwei Ji, Yuzhe Gu, Wenwei Zhang et al.
Mitigating Hallucinations in Large Vision-Language Models (LVLMs) via Language-Contrastive Decoding (LCD)
Avshalom Manevich, Reut Tsarfaty
Leveraging Graph Structures to Detect Hallucinations in Large Language Models
Noa Nonkes, Sergei Agaronian, Evangelos Kanoulas et al.
Halwasa: Quantify and Analyze Hallucinations in Large Language Models: Arabic as a Case Study
Hamdy Mubarak, Hend Al-Khalifa, Khaloud Suliman Alkhalefah
Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding
Sicong Leng, Hang Zhang, Guanzheng Chen et al.
Contrastive Decoding Reduces Hallucinations in Large Multilingual Machine Translation Models
Jonas Waldendorf, Barry Haddow, Alexandra Birch
Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps
Yung-Sung Chuang, Linlu Qiu, Cheng-Yu Hsieh et al.
Whispers that Shake Foundations: Analyzing and Mitigating False Premise Hallucinations in Large Language Models
Hongbang Yuan, Pengfei Cao, Zhuoran Jin et al.
FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models
Liqiang Jing, Ruosen Li, Yunmo Chen et al.
EFUF: Efficient Fine-Grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models
Shangyu Xing, Fei Zhao, Zhen Wu et al.
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space
Shaolei Zhang, Tian Yu, Yang Feng