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06/19/2023
Parallel Data Compression Techniques
With endless amounts of data and very limited bandwidth, fast data compr...
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04/17/2023
Bridging Discrete and Backpropagation: Straight-Through and Beyond
Backpropagation, the cornerstone of deep learning, is limited to computi...
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06/14/2022
SoTeacher: A Student-oriented Teacher Network Training Framework for Knowledge Distillation
How to train an ideal teacher for knowledge distillation is still an ope...
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02/15/2022
PILED: An Identify-and-Localize Framework for Few-Shot Event Detection
Practical applications of event extraction systems have long been hinder...
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10/07/2021
Double Descent in Adversarial Training: An Implicit Label Noise Perspective
Here, we show that the robust overfitting shall be viewed as the early p...
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06/21/2021
Empower Distantly Supervised Relation Extraction with Collaborative Adversarial Training
With recent advances in distantly supervised (DS) relation extraction (R...
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06/17/2021
Multi-head or Single-head? An Empirical Comparison for Transformer Training
Multi-head attention plays a crucial role in the recent success of Trans...
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05/28/2021
UCPhrase: Unsupervised Context-aware Quality Phrase Tagging
Identifying and understanding quality phrases from context is a fundamen...
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02/15/2021
Data Profiling for Adversarial Training: On the Ruin of Problematic Data
Multiple intriguing problems hover in adversarial training, including ro...
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10/15/2020
Overfitting or Underfitting? Understand Robustness Drop in Adversarial Training
Our goal is to understand why the robustness drops after conducting adve...
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08/18/2020
Very Deep Transformers for Neural Machine Translation
We explore the application of very deep Transformer models for Neural Ma...
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05/01/2020
Partially-Typed NER Datasets Integration: Connecting Practice to Theory
While typical named entity recognition (NER) models require the training...
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04/17/2020
Understanding the Difficulty of Training Transformers
Transformers have been proved effective for many deep learning tasks. Tr...
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10/09/2019
Learning to Contextually Aggregate Multi-Source Supervision for Sequence Labeling
Sequence labeling is a fundamental framework for various natural languag...
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09/03/2019
CrossWeigh: Training Named Entity Tagger from Imperfect Annotations
Everyone makes mistakes. So do human annotators when curating labels for...
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08/27/2019
Facet-Aware Evaluation for Extractive Text Summarization
Commonly adopted metrics for extractive text summarization like ROUGE fo...
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08/14/2019
Raw-to-End Name Entity Recognition in Social Media
Taking word sequences as the input, typical named entity recognition (NE...
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08/08/2019
On the Variance of the Adaptive Learning Rate and Beyond
The learning rate warmup heuristic achieves remarkable success in stabil...
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04/19/2019
Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction
In recent years there is surge of interest in applying distant supervisi...
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12/27/2018
Cross-relation Cross-bag Attention for Distantly-supervised Relation Extraction
Distant supervision leverages knowledge bases to automatically label ins...
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09/10/2018
Learning Named Entity Tagger using Domain-Specific Dictionary
Recent advances in deep neural models allow us to build reliable named e...
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04/20/2018
Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling
Many efforts have been made to facilitate natural language processing ta...
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03/09/2018
Expert Finding in Heterogeneous Bibliographic Networks with Locally-trained Embeddings
Expert finding is an important task in both industry and academia. It is...
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12/19/2017
Wikidata Vandalism Detection - The Loganberry Vandalism Detector at WSDM Cup 2017
Wikidata is the new, large-scale knowledge base of the Wikimedia Foundat...
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09/13/2017
Empower Sequence Labeling with Task-Aware Neural Language Model
Linguistic sequence labeling is a general modeling approach that encompa...
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07/01/2017