15 citations · 21 across the 11 of their papers we have counts for
11 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…
Does Memory Need Graphs? A Unified Framework and Empirical Analysis for Long-Term Dialog Memory
Sen Hu, Yuxiang Wei, Jiaxin Ran +5
Graph structures are increasingly used in dialog memory systems, but empirical findings on their effectiveness remain inconsistent, making it unclear which design choices truly mat…
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…
Exploiting Prefix-Tree in Structured Output Interfaces for Enhancing Jailbreak Attacking
Yanzeng Li, Yunfan Xiong, Jialun Zhong +3
The rise of Large Language Models (LLMs) has led to significant applications but also introduced serious security threats, particularly from jailbreak attacks that manipulate outpu…
DySpec: Faster Speculative Decoding with Dynamic Token Tree Structure
Yunfan Xiong, Ruoyu Zhang, Yanzeng Li +2
While speculative decoding has recently appeared as a promising direction for accelerating the inference of large language models (LLMs), the speedup and scalability are strongly b…
MedDiT: A Knowledge-Controlled Diffusion Transformer Framework for Dynamic Medical Image Generation in Virtual Simulated Patient
Yanzeng Li, Cheng Zeng, Jinchao Zhang +2
Medical education relies heavily on Simulated Patients (SPs) to provide a safe environment for students to practice clinical skills, including medical image analysis. However, the…
MMPKUBase: A Comprehensive and High-quality Chinese Multi-modal Knowledge Graph
Xuan Yi, Yanzeng Li, Lei Zou
Multi-modal knowledge graphs have emerged as a powerful approach for information representation, combining data from different modalities such as text, images, and videos. While se…
Leveraging Large Language Model as Simulated Patients for Clinical Education
Yanzeng Li, Cheng Zeng, Jialun Zhong +3
Simulated Patients (SPs) play a crucial role in clinical medical education by providing realistic scenarios for student practice. However, the high cost of training and hiring qual…
LLMaAA: Making Large Language Models as Active Annotators
Ruoyu Zhang, Yanzeng Li, Yongliang Ma +2
Prevalent supervised learning methods in natural language processing (NLP) are notoriously data-hungry, which demand large amounts of high-quality annotated data. In practice, acqu…
Two is Better Than One: Answering Complex Questions by Multiple Knowledge Sources with Generalized Links
Minhao Zhang, Yongliang Ma, Yanzeng Li +3
Incorporating multiple knowledge sources is proven to be beneficial for answering complex factoid questions. To utilize multiple knowledge bases (KB), previous works merge all KBs…