1 citations · 1 across the 9 of their papers we have counts for
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A Generative Model for Joint Multiple Intent Detection and Slot Filling
Liz Li, Wei Zhu
In task-oriented dialogue systems, spoken language understanding (SLU) is a critical component, which consists of two sub-tasks, intent detection and slot filling. Most existing me…
ACL: Aligned Contrastive Learning Improves BERT and Multi-exit BERT Fine-tuning
Liz Li, Wei Zhu
Despite its success in self-supervised learning, contrastive learning is less studied in the supervised setting. In this work, we first use a set of pilot experiments to show that…
Pursuing Best Industrial Practices for Retrieval-Augmented Generation in the Medical Domain
Liz Li, Wei Zhu
While retrieval augmented generation (RAG) has been swiftly adopted in industrial applications based on large language models (LLMs), there is no consensus on what are the best pra…
Evaluating ChatGPT on Medical Information Extraction Tasks: Performance, Explainability and Beyond
Liz Li, Wei Zhu
Large Language Models (LLMs) like ChatGPT have demonstrated amazing capabilities in comprehending user intents and generate reasonable and useful responses. Beside their ability to…
MRAG: Benchmarking Retrieval-Augmented Generation for Bio-medicine
Liz Li, Wei Zhu
While Retrieval-Augmented Generation (RAG) has been swiftly adopted in scientific and clinical QA systems, a comprehensive evaluation benchmark in the medical domain is lacking. To…
From Implicit to Explicit: Enhancing Self-Recognition in Large Language Models
Yinghan Zhou, Weifeng Zhu, Juan Wen +3
Large language models (LLMs) have been shown to possess a degree of self-recognition ability, which used to identify whether a given text was generated by themselves. Prior work ha…