8 papers
RAGOCR: Optical Compression of Retrieval-Augmented Text via Visual Representation
Jiayang Yu, Jialun Zhong, Lei Zou
Retrieval-Augmented Generation (RAG) has become essential for knowledge-intensive question answering, yet scaling RAG pipelines remains challenging due to the prohibitive computati…
SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs
Hao Wang, Jialun Zhong, Changcheng Wang +5
Knowledge-based conversational question answering (KBCQA) confronts persistent challenges in resolving coreference, modeling contextual dependencies, and executing complex logical…
DySRec: Dynamic Context-Aware Psychometric Scale Recommendation via Multi-Agent Collaboration
Yanzeng Li, Xiaoning Cao, Jialun Zhong +5
Choosing suitable psychometric scales is an essential and difficult step in psychological consultation, which requires clinicians to integrate patient information, behaviors, and d…
Detecting Hallucinations in Retrieval-Augmented Generation via Semantic-level Internal Reasoning Graph
Jianpeng Hu, Yanzeng Li, Jialun Zhong +2
The Retrieval-augmented generation (RAG) system based on Large language model (LLM) has made significant progress. It can effectively reduce factuality hallucinations, but faithful…
GAP: Graph-Assisted Prompts for Dialogue-based Medication Recommendation
Jialun Zhong, Yanzeng Li, Sen Hu +3
Medication recommendations have become an important task in the healthcare domain, especially in measuring the accuracy and safety of medical dialogue systems (MDS). Different from…
A Comprehensive Survey of Reward Models: Taxonomy, Applications, Challenges, and Future
Jialun Zhong, Wei Shen, Yanzeng Li +7
Reward Model (RM) has demonstrated impressive potential for enhancing Large Language Models (LLM), as RM can serve as a proxy for human preferences, providing signals to guide LLMs…