From the 1 of 4 linked papers with an AI index.
4 papers
VIG-RL: Learning to Search and Insert for Verified Image Grounding
Qinhan Yu, Jun Guang, Chong Chen +1
The paper introduces VIG-RL, a reinforcement‑learning based agent that dynamically decides when to retrieve, select, and insert authentic images into text responses, improving veri…
Beyond Explicit Refusals: Soft-Failure Attacks on Retrieval-Augmented Generation
Wentao Zhang, Yan Zhuang, ZhuHang Zheng +3
Existing jamming attacks on Retrieval-Augmented Generation (RAG) systems typically induce explicit refusals or denial-of-service behaviors, which are conspicuous and easy to detect…
M2IO-R1: An Efficient RL-Enhanced Reasoning Framework for Multimodal Retrieval Augmented Multimodal Generation
Zhiyou Xiao, Qinhan Yu, Binghui Li +3
Current research on Multimodal Retrieval-Augmented Generation (MRAG) enables diverse multimodal inputs but remains limited to single-modality outputs, restricting expressive capaci…
Training-free Heterogeneous Graph Condensation via Data Selection
Yuxuan Liang, Wentao Zhang, Xinyi Gao +5
Efficient training of large-scale heterogeneous graphs is of paramount importance in real-world applications. However, existing approaches typically explore simplified models to mi…