20 citations · 45 across the 12 of their papers we have counts for
12 papers
Efficient Sub-structured Knowledge Distillation
Wenye Lin, Yangming Li, Lemao Liu +2
Structured prediction models aim at solving a type of problem where the output is a complex structure, rather than a single variable. Performing knowledge distillation for such mod…
Rethinking Negative Sampling for Handling Missing Entity Annotations
Yangming Li, Lemao Liu, Shuming Shi
Negative sampling is highly effective in handling missing annotations for named entity recognition (NER). One of our contributions is an analysis on how it makes sense through intr…
Neural Sequence Segmentation as Determining the Leftmost Segments
Yangming Li, Lemao Liu, Kaisheng Yao
Prior methods to text segmentation are mostly at token level. Despite the adequacy, this nature limits their full potential to capture the long-term dependencies among segments. In…
TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis
Haisong Zhang, Lemao Liu, Haiyun Jiang +14
This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities. Com…
Interpretable NLG for Task-oriented Dialogue Systems with Heterogeneous Rendering Machines
Yangming Li, Kaisheng Yao
End-to-end neural networks have achieved promising performances in natural language generation (NLG). However, they are treated as black boxes and lack interpretability. To address…
Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition
Yangming Li, Lemao Liu, Shuming Shi
In many scenarios, named entity recognition (NER) models severely suffer from unlabeled entity problem, where the entities of a sentence may not be fully annotated. Through empiric…