新方法增强多模态模型用于视觉问答 · 跟踪 6 个来源

报道来源 [6]

1. arXiv cs.AI TIER_1 English(EN) · Marco Morini, Sara Sarto, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara · 2026-08-07 04:00

   再看一遍：面向知识型视觉问答的无训练证据高亮

   arXiv:2604.01280v2 Announce Type: replace-cross Abstract: Knowledge-based Visual Question Answering (KB-VQA) requires Multimodal Large Language Models (MLLMs) to identify and combine fine-grained visual cues with retrieved textual evidence. However, retrieval often introduces noi…

2. arXiv cs.LG TIER_1 English(EN) · Jingchen Sun, Shaobo Han, Ruiyi Zhang, Naresh Kumar Devulapally, Ming Liu, Yitao Long, Vishnu Suresh Lokhande, Changyou Chen · 2026-08-05 04:00

   贝叶斯数据重加权改进基于知识的视觉问答的多模态检索

   arXiv:2608.02907v1 Announce Type: new Abstract: Multimodal retrievers are essential for knowledge-based visual question answering, where they retrieve external evidence for image-question pairs. However, existing contrastive training methods typically treat all unmatched query-do…

3. arXiv cs.CL TIER_1 English(EN) · Ganzhong Luo, Yang Ren, Hanyong Wang, Shuyu Zheng, Menglong Yang · 2026-08-04 04:00

   UniHEAR：统一的异构源注意力检索用于知识驱动的视觉问答

   arXiv:2608.01147v1 Announce Type: cross Abstract: Knowledge-Based Visual Question Answering (KB-VQA) requires retrieving relevant entity knowledge from external sources to answer visually grounded questions. Existing retrieval-augmented systems suffer from two critical limitation…

4. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Menglong Yang · 2026-08-02 10:57

   UniHEAR：统一的异构源注意力检索用于知识驱动的视觉问答

   Knowledge-Based Visual Question Answering (KB-VQA) requires retrieving relevant entity knowledge from external sources to answer visually grounded questions. Existing retrieval-augmented systems suffer from two critical limitations. First, relying on a single retrieval modality c…

5. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Menglong Yang · 2026-08-02 10:57

   UniHEAR：统一的异构源注意力检索用于知识驱动的视觉问答

   Knowledge-Based Visual Question Answering (KB-VQA) requires retrieving entity knowledge from external sources to answer visually grounded questions. Existing retrieval-augmented systems suffer from two critical limitations. First, relying on a single retrieval modality creates a …

6. arXiv cs.CV TIER_1 English(EN) · Haokun Wen, Xuemeng Song, Haoyu Zhang, Weili Guan, Xiangyu Zhao, Liqiang Nie · 2026-08-04 04:00

   UniCVR：从对齐到重排，实现统一的零样本组合视觉检索

   arXiv:2604.20318v2 Announce Type: replace Abstract: Composed image retrieval, multi-turn composed image retrieval, and composed video retrieval all share a common paradigm: composing the reference visual with modification text to retrieve the desired target. Despite this shared s…