视觉大模型 / VLM

Adaptive Cache Enhancement for Test-Time Adaptation of Vision-Language Models

Khanh-Binh Nguyen, Phuoc-Nguyen Bui, Hyunseung Choo, Duc Thanh Nguyen

机构 * Deakin University（德克萨斯大学） ； Sungkyunkwan University（成均馆大学） 纠错

专题命中 幻觉与鲁棒性 ：vision-language model(title,abstract)；分类 cs.CV

Comments 12 pages, Under review

Res-Bench: Benchmarking the Robustness of Multimodal Large Language Models to Dynamic Resolution Input

Chenxu Li, Zhicai Wang, Yuan Sheng, Xingyu Zhu, Yanbin Hao, Xiang Wang

专题命中 幻觉与鲁棒性 ：multimodal large language model(title,abstract)；分类 cs.CV

Comments 23 pages

Leveraging NTPs for Efficient Hallucination Detection in VLMs

Ofir Azachi, Kfir Eliyahu, Eyal El Ani, Rom Himelstein, Roi Reichart, Yuval Pinter, Nitay Calderon

机构 * Department of Data and Decision Science, Technion - Israel Institute of Technology（数据与决策科学系，技术学院-以色列理工学院） ； Faculty of Computer and Information Science, Ben-Gurion University of the Negev（计算机与信息科学系，贝内-约尔根大学） 纠错

专题命中 幻觉与鲁棒性 ：vision-language model(abstract)；VLM(abstract)；分类 cs.CV、cs.LG

Comments Accepted to The First Workshop on Confabulation, Hallucinations, & Overgeneration in Multilingual & Precision-critical Setting - AACL-IJCNLP2025

AUVIC: Adversarial Unlearning of Visual Concepts for Multi-modal Large Language Models

Haokun Chen, Jianing Li, Yao Zhang, Jinhe Bi, Yan Xia, Jindong Gu, Volker Tresp

专题命中 幻觉与鲁棒性 ：multimodal large language model(abstract)；分类 cs.CV、cs.AI

Comments AAAI 2026. Code: https://github.com/HaokunChen245/AUVIC

Guarding the Meaning: Self-Supervised Training for Semantic Robustness in Guard Models

Cristina Pinneri, Christos Louizos

机构 * Qualcomm AI Research（高通人工智能研究） 纠错

专题命中 幻觉与鲁棒性 ：grounding(abstract)；分类 cs.AI、cs.LG

AccKV: Towards Efficient Audio-Video LLMs Inference via Adaptive-Focusing and Cross-Calibration KV Cache Optimization

Zhonghua Jiang, Kui Chen, Kunxi Li, Keting Yin, Yiyun Zhou, Zhaode Wang, Chengfei Lv, Shengyu Zhang

专题命中 幻觉与鲁棒性 ：visual question answering(abstract)；分类 cs.CV

Preserving Cross-Modal Consistency for CLIP-based Class-Incremental Learning

Haoran Chen, Houze Xu, Micah Goldblum, Daoguo Dong, Zuxuan Wu

机构 * Institute of Trustworthy Embodied AI（可信具身人工智能研究院） ； Fudan University（复旦大学） ； Shanghai Collaborative Innovation Center of Intelligent Visual Computing（上海智能视觉计算协同创新中心） ； Columbia University（哥伦比亚大学） 纠错

专题命中 幻觉与鲁棒性 ：vision-language model(abstract)；分类 cs.CV