3.7k citations · 3.7k across the 4 of their papers we have counts for
4 papers
iTAG: Inverse Design for Natural Text Generation with Accurate Causal Graph Annotations
Wenshuo Wang, Boyu Cao, Nan Zhuang +1
A fundamental obstacle to causal discovery from text is the lack of causally annotated text data for use as ground truth, due to high annotation costs. This motivates an important…
DiaKG: an Annotated Diabetes Dataset for Medical Knowledge Graph Construction
Dejie Chang, Mosha Chen, Chaozhen Liu +9
Knowledge Graph has been proven effective in modeling structured information and conceptual knowledge, especially in the medical domain. However, the lack of high-quality annotated…
Do Transformer Modifications Transfer Across Implementations and Applications?
Sharan Narang, Hyung Won Chung, Yi Tay +13
The research community has proposed copious modifications to the Transformer architecture since it was introduced over three years ago, relatively few of which have seen widespread…
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts +6
Transfer learning, where a model is first pre-trained on a data-rich task before being fine-tuned on a downstream task, has emerged as a powerful technique in natural language proc…