6 papers
RAR: Retrieval-Augmented Medical Reasoning via Thought-Driven Retrieval
Kaishuai Xu, Wenjun Hou, Yi Cheng +1
Large Language Models (LLMs) have shown promising performance on diverse medical benchmarks, highlighting their potential in supporting real-world clinical tasks. Retrieval-Augment…
AutoPal: Autonomous Adaptation to Users for Personal AI Companionship
Yi Cheng, Wenge Liu, Kaishuai Xu +6
Previous research has demonstrated the potential of AI agents to act as companions that can provide constant emotional support for humans. In this paper, we emphasize the necessity…
RADAR: Enhancing Radiology Report Generation with Supplementary Knowledge Injection
Wenjun Hou, Yi Cheng, Kaishuai Xu +4
Large language models (LLMs) have demonstrated remarkable capabilities in various domains, including radiology report generation. Previous approaches have attempted to utilize mult…
Learning to Align Multi-Faceted Evaluation: A Unified and Robust Framework
Kaishuai Xu, Tiezheng Yu, Wenjun Hou +6
Large Language Models (LLMs) are being used more and more extensively for automated evaluation in various scenarios. Previous studies have attempted to fine-tune open-source LLMs t…
Subtle Errors in Reasoning: Preference Learning via Error-injected Self-editing
Kaishuai Xu, Tiezheng Yu, Wenjun Hou +7
Large Language Models (LLMs) have exhibited strong mathematical reasoning prowess, tackling tasks ranging from basic arithmetic to advanced competition-level problems. However, fre…
Integrative Decoding: Improve Factuality via Implicit Self-consistency
Yi Cheng, Xiao Liang, Yeyun Gong +11
Self-consistency-based approaches, which involve repeatedly sampling multiple outputs and selecting the most consistent one as the final response, prove to be remarkably effective…