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07/20/2023
Performance Issue Identification in Cloud Systems with Relational-Temporal Anomaly Detection
Performance issues permeate large-scale cloud service systems, which can...
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06/02/2023
EvLog: Evolving Log Analyzer for Anomalous Logs Identification
Software logs record system activities, aiding maintainers in identifyin...
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05/23/2023
Validating Multimedia Content Moderation Software via Semantic Fusion
The exponential growth of social media platforms, such as Facebook and T...
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05/21/2023
BiasAsker: Measuring the Bias in Conversational AI System
Powered by advanced Artificial Intelligence (AI) techniques, conversatio...
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03/15/2023
ChatGPT or Grammarly? Evaluating ChatGPT on Grammatical Error Correction Benchmark
ChatGPT is a cutting-edge artificial intelligence language model develop...
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02/11/2023
MTTM: Metamorphic Testing for Textual Content Moderation Software
The exponential growth of social media platforms such as Twitter and Fac...
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03/16/2022
Understanding and Improving Sequence-to-Sequence Pretraining for Neural Machine Translation
In this paper, we present a substantial step in better understanding the...
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12/23/2021
Revisiting, Benchmarking and Exploring API Recommendation: How Far Are We?
Application Programming Interfaces (APIs), which encapsulate the impleme...
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06/16/2021
Discrete Auto-regressive Variational Attention Models for Text Modeling
Variational autoencoders (VAEs) have been widely applied for text modeli...
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05/08/2021
HiTyper: A Hybrid Static Type Inference Framework with Neural Prediction
Type inference for dynamic programming languages is an important yet cha...
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10/24/2020
Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation
Non-Autoregressive machine Translation (NAT) models have demonstrated si...
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10/09/2020
Learning 3D Face Reconstruction with a Pose Guidance Network
We present a self-supervised learning approach to learning monocular 3D ...
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04/24/2020
Why an Android App is Classified as Malware? Towards Malware Classification Interpretation
Machine learning (ML) based approach is considered as one of the most pr...
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04/21/2020
Discrete Variational Attention Models for Language Generation
Variational autoencoders have been widely applied for natural language g...
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04/05/2020
Flow2Stereo: Effective Self-Supervised Learning of Optical Flow and Stereo Matching
In this paper, we propose a unified method to jointly learn optical flow...
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11/21/2019
Few Shot Network Compression via Cross Distillation
Model compression has been widely adopted to obtain light-weighted deep ...
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09/05/2019
Detecting Deep Neural Network Defects with Data Flow Analysis
Deep neural networks (DNNs) are shown to be promising solutions in many ...
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04/19/2019
SelFlow: Self-Supervised Learning of Optical Flow
We present a self-supervised learning approach for optical flow. Our met...
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11/11/2016
