1 citations · 1 across the 3 of their papers we have counts for
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Improving Prediction Backward-Compatiblility in NLP Model Upgrade with Gated Fusion
Yi-An Lai, Elman Mansimov, Yuqing Xie +1
When upgrading neural models to a newer version, new errors that were not encountered in the legacy version can be introduced, known as regression errors. This inconsistent behavio…
Efficient Domain Adaptation of Language Models via Adaptive Tokenization
Vin Sachidananda, Jason S. Kessler, Yi-an Lai
Contextual embedding-based language models trained on large data sets, such as BERT and RoBERTa, provide strong performance across a wide range of tasks and are ubiquitous in moder…
Regression Bugs Are In Your Model! Measuring, Reducing and Analyzing Regressions In NLP Model Updates
Yuqing Xie, Yi-an Lai, Yuanjun Xiong +2
Behavior of deep neural networks can be inconsistent between different versions. Regressions during model update are a common cause of concern that often over-weigh the benefits in…
Diversity, Density, and Homogeneity: Quantitative Characteristic Metrics for Text Collections
Yi-An Lai, Xuan Zhu, Yi Zhang +1
Summarizing data samples by quantitative measures has a long history, with descriptive statistics being a case in point. However, as natural language processing methods flourish, t…
Goal-Embedded Dual Hierarchical Model for Task-Oriented Dialogue Generation
Yi-An Lai, Arshit Gupta, Yi Zhang
Hierarchical neural networks are often used to model inherent structures within dialogues. For goal-oriented dialogues, these models miss a mechanism adhering to the goals and negl…