4 citations · 4 across the 6 of their papers we have counts for
6 papers
OOPrompt: Reifying Intents into Structured Artifacts for Modular and Iterative Prompting
Tengyou Xu, Detao Ma, Xiang 'Anthony' Chen
The rise of large language models (LLMs) has given rise to a class of prompt-based interactive systems where users primarily express their input in natural language. However, compo…
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…
Are LLM-based Evaluators Confusing NLG Quality Criteria?
Xinyu Hu, Mingqi Gao, Sen Hu +4
Some prior work has shown that LLMs perform well in NLG evaluation for different tasks. However, we discover that LLMs seem to confuse different evaluation criteria, which reduces…
From Beginner to Expert: Modeling Medical Knowledge into General LLMs
Qiang Li, Xiaoyan Yang, Haowen Wang +14
Recently, large language model (LLM) based artificial intelligence (AI) systems have demonstrated remarkable capabilities in natural language understanding and generation. However,…
S2M: Converting Single-Turn to Multi-Turn Datasets for Conversational Question Answering
Baokui Li, Sen Zhang, Wangshu Zhang +6
Supplying data augmentation to conversational question answering (CQA) can effectively improve model performance. However, there is less improvement from single-turn datasets in CQ…
AdapterDistillation: Non-Destructive Task Composition with Knowledge Distillation
Junjie Wang, Yicheng Chen, Wangshu Zhang +3
Leveraging knowledge from multiple tasks through introducing a small number of task specific parameters into each transformer layer, also known as adapters, receives much attention…