7 papers
Rethinking Soft Compression in Retrieval-Augmented Generation: A Query-Conditioned Selector Perspective
Yunhao Liu, Zian Jia, Xinyu Gao +2
Retrieval-Augmented Generation (RAG) effectively grounds Large Language Models (LLMs) with external knowledge and is widely applied to Web-related tasks. However, its scalability i…
A.E. Convergence vs Boundedness
Xinyu Gao, Loukas Grafakos
We extend Stein's maximal theorem to the bilinear setting. Let be a homogeneous space with a transitive action of a compact abelian group, and let and $1/2 \l…
Gated Tree Cross-Attention for Checkpoint-Compatible Syntax Injection in Decoder-Only LLMs
Xinyu Gao, Shaonan Wang, Nai Ding
Decoder-only large language models achieve strong broad performance but are brittle to minor grammatical perturbations, undermining reliability for downstream reasoning. However, d…
TA-KAND: Two-stage Attention Triple Enhancement and U-KAN based Diffusion For Few-shot Knowledge Graph Completion
Xinyu Gao
Knowledge Graphs have become fundamental infrastructure for applications such as intelligent question answering and recommender systems due to their expressive representation. Neve…
DCMI: A Differential Calibration Membership Inference Attack Against Retrieval-Augmented Generation
Xinyu Gao, Xiangtao Meng, Yingkai Dong +2
While Retrieval-Augmented Generation (RAG) effectively reduces hallucinations by integrating external knowledge bases, it introduces vulnerabilities to membership inference attacks…
The Devil is in the Prompts: Retrieval-Augmented Prompt Optimization for Text-to-Video Generation
Bingjie Gao, Xinyu Gao, Xiaoxue Wu +5
The evolution of Text-to-video (T2V) generative models, trained on large-scale datasets, has been marked by significant progress. However, the sensitivity of T2V generative models…