4 citations · 8 across the 5 of their papers we have counts for
5 papers
LG-LSQ: Learned Gradient Linear Symmetric Quantization
Shih-Ting Lin, Zhaofang Li, Yu-Hsiang Cheng +3
Deep neural networks with lower precision weights and operations at inference time have advantages in terms of the cost of memory space and accelerator power. The main challenge as…
Conditional Generation of Temporally-ordered Event Sequences
Shih-Ting Lin, Nathanael Chambers, Greg Durrett
Models of narrative schema knowledge have proven useful for a range of event-related tasks, but they typically do not capture the temporal relationships between events. We propose…
ReadOnce Transformers: Reusable Representations of Text for Transformers
Shih-Ting Lin, Ashish Sabharwal, Tushar Khot
We present ReadOnce Transformers, an approach to convert a transformer-based model into one that can build an information-capturing, task-independent, and compressed representation…
Effective Distant Supervision for Temporal Relation Extraction
Xinyu Zhao, Shih-ting Lin, Greg Durrett
A principal barrier to training temporal relation extraction models in new domains is the lack of varied, high quality examples and the challenge of collecting more. We present a m…
Tradeoffs in Sentence Selection Techniques for Open-Domain Question Answering
Shih-Ting Lin, Greg Durrett
Current methods in open-domain question answering (QA) usually employ a pipeline of first retrieving relevant documents, then applying strong reading comprehension (RC) models to t…