5 papers
The Dialogue That Heals: A Comprehensive Evaluation of Doctor Agents' Inquiry Capability
Linlu Gong, Ante Wang, Yunghwei Lai +2
An effective physician should possess a combination of empathy, expertise, patience, and clear communication when treating a patient. Recent advances have successfully endowed AI d…
Patient-Zero: Scaling Synthetic Patient Agents to Real-World Distributions without Real Patient Data
Yunghwei Lai, Ziyue Wang, Weizhi Ma +1
Synthetic data generation with Large Language Models (LLMs) has emerged as a promising solution in the medical domain to mitigate data scarcity and privacy constraints. However, ex…
StoryBench: A Dynamic Benchmark for Evaluating Long-Term Memory with Multi Turns
Luanbo Wan, Weizhi Ma
Long-term memory (LTM) is essential for large language models (LLMs) to achieve autonomous intelligence in complex, evolving environments. Despite increasing efforts in memory-augm…
Towards Transparent RAG: Fostering Evidence Traceability in LLM Generation via Reinforcement Learning
Jingyi Ren, Yekun Xu, Xiaolong Wang +4
Retrieval-Augmented Generation (RAG) delivers substantial value in knowledge-intensive applications. However, its generated responses often lack transparent reasoning paths that tr…
Efficient Dynamic Clustering-Based Document Compression for Retrieval-Augmented-Generation
Weitao Li, Kaiming Liu, Xiangyu Zhang +3
Retrieval-Augmented Generation (RAG) has emerged as a widely adopted approach for knowledge injection during large language model (LLM) inference in recent years. However, due to t…