5 papers · 1 filter
RING: Retrieval-Internalized Generation for Continual Large-Scale Knowledge Injection
Shicheng Xu, Liang Pang, Liyi Chen +7
Retrieval-augmented generation (RAG) improves factuality but adds latency and engineering overhead at serving time. We propose RING (Retrieval-Internalized Generation), a holistic…
Aligning Large Language Models with Searcher Preferences
Wei Wu, Peilun Zhou, Liyi Chen +6
The paradigm shift from item-centric ranking to answer-centric synthesis is redefining the role of search engines. While recent industrial progress has applied generative technique…
DecEx-RAG: Boosting Agentic Retrieval-Augmented Generation with Decision and Execution Optimization via Process Supervision
Yongqi Leng, Yikun Lei, Xikai Liu +7
Agentic Retrieval-Augmented Generation (Agentic RAG) enhances the processing capability for complex tasks through dynamic retrieval and adaptive workflows. Recent advances (e.g., S…
RealBench: A Chinese Multi-image Understanding Benchmark Close to Real-world Scenarios
Fei Zhao, Chengqiang Lu, Yufan Shen +9
While various multimodal multi-image evaluation datasets have been emerged, but these datasets are primarily based on English, and there has yet to be a Chinese multi-image dataset…
SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment
Yuqing Huang, Rongyang Zhang, Qimeng Wang +9
Recent advancements in large language models (LLMs) have revolutionized natural language processing through their remarkable capabilities in understanding and executing diverse tas…