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05/10/2023
Efficient Training of Multi-task Neural Solver with Multi-armed Bandits
Efficiently training a multi-task neural solver for various combinatoria...
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03/20/2023
Targeted Analysis of High-Risk States Using an Oriented Variational Autoencoder
Variational autoencoder (VAE) neural networks can be trained to generate...
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11/12/2022
Analysis of Graph Neural Networks with Theory of Markov Chains
In this paper, we provide a theoretical tool for the interpretation and ...
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10/26/2022
Benchmarking Language Models for Code Syntax Understanding
Pre-trained language models have demonstrated impressive performance in ...
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10/25/2022
IELM: An Open Information Extraction Benchmark for Pre-Trained Language Models
We introduce a new open information extraction (OIE) benchmark for pre-t...
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10/18/2022
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models
Deep Neural Networks (DNNs) are known to be vulnerable to backdoor attac...
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09/19/2022
Joint Language Semantic and Structure Embedding for Knowledge Graph Completion
The task of completing knowledge triplets has broad downstream applicati...
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09/08/2022
Generating Contextual Load Profiles Using a Conditional Variational Autoencoder
Generating power system states that have similar distribution and depend...
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05/21/2022
DeepStruct: Pretraining of Language Models for Structure Prediction
We introduce a method for improving the structural understanding abiliti...
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12/05/2021
Protecting Intellectual Property of Language Generation APIs with Lexical Watermark
Nowadays, due to the breakthrough in natural language generation (NLG), ...
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10/21/2021
Generating Multivariate Load States Using a Conditional Variational Autoencoder
For planning of power systems and for the calibration of operational too...
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09/23/2021
Zero-Shot Information Extraction as a Unified Text-to-Triple Translation
We cast a suite of information extraction tasks into a text-to-triple tr...
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03/24/2021
Graph Representation Learning by Ensemble Aggregating Subgraphs via Mutual Information Maximization
Graph Neural Networks have shown tremendous potential on dealing with ga...
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10/22/2020
Language Models are Open Knowledge Graphs
This paper shows how to construct knowledge graphs (KGs) from pre-traine...
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03/04/2020
Detection of False Data Injection Attacks Using the Autoencoder Approach
The security of supply in a power grid critically depends on the ability...
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02/14/2020
Transformer on a Diet
Transformer has been widely used thanks to its ability to capture sequen...
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12/02/2019
Meta-Path Constrained Random Walk Inference for Large-Scale Heterogeneous Information Networks
Heterogeneous information network (HIN) has shown its power of modeling ...
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11/09/2019
PoD: Positional Dependency-Based Word Embedding for Aspect Term Extraction
Dependency context-based word embedding jointly learns the representatio...
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10/08/2019
Percentile-Based Residuals for Model Assessment
Residuals are a key component of diagnosing model fit. The usual practic...
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07/09/2019
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
We present GluonCV and GluonNLP, the deep learning toolkits for computer...
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04/20/2019
Language Models with Transformers
The Transformer architecture is superior to RNN-based models in computat...
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07/30/2016