16 citations · 26 across the 4 of their papers we have counts for
4 papers
Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events
Yu Gu, Sheng Zhang, Naoto Usuyama +8
Large language models (LLMs), such as GPT-4, have demonstrated remarkable capabilities across a wide range of tasks, including health applications. In this paper, we study how LLMs…
Benchmarking Diverse-Modal Entity Linking with Generative Models
Sijia Wang, Alexander Hanbo Li, Henry Zhu +9
Entities can be expressed in diverse formats, such as texts, images, or column names and cell values in tables. While existing entity linking (EL) models work well on per modality…
Compositional Zero-Shot Domain Transfer with Text-to-Text Models
Fangyu Liu, Qianchu Liu, Shruthi Bannur +9
Label scarcity is a bottleneck for improving task performance in specialised domains. We propose a novel compositional transfer learning framework (DoT5 - domain compositional zero…
Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness
Shuaichen Chang, Jun Wang, Mingwen Dong +13
Neural text-to-SQL models have achieved remarkable performance in translating natural language questions into SQL queries. However, recent studies reveal that text-to-SQL models ar…