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05/29/2023
ACETest: Automated Constraint Extraction for Testing Deep Learning Operators
Deep learning (DL) applications are prevalent nowadays as they can help ...
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12/05/2022
SASFormer: Transformers for Sparsely Annotated Semantic Segmentation
Semantic segmentation based on sparse annotation has advanced in recent ...
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09/21/2022
WeLM: A Well-Read Pre-trained Language Model for Chinese
Large Language Models pre-trained with self-supervised learning have dem...
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08/03/2022
Re-Attention Transformer for Weakly Supervised Object Localization
Weakly supervised object localization is a challenging task which aims t...
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06/14/2022
Temporal Multimodal Multivariate Learning
We introduce temporal multimodal multivariate learning, a new family of ...
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12/16/2021
Knowledge-enhanced Session-based Recommendation with Temporal Transformer
Recent research has achieved impressive progress in the session-based re...
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06/07/2021
Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study
Recent advancements in open-domain question answering (ODQA), i.e., find...
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03/22/2021
Complementary Evidence Identification in Open-Domain Question Answering
This paper proposes a new problem of complementary evidence identificati...
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02/06/2021
Neural Data-to-Text Generation with LM-based Text Augmentation
For many new application domains for data-to-text generation, the main o...
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11/14/2020
Patient-Specific Seizure Prediction Using Single Seizure Electroencephalography Recording
Electroencephalogram (EEG) is a prominent way to measure the brain activ...
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10/18/2020
Deep Structured Prediction for Facial Landmark Detection
Existing deep learning based facial landmark detection methods have achi...
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07/20/2020
Multimodal Dialogue State Tracking By QA Approach with Data Augmentation
Recently, a more challenging state tracking task, Audio-Video Scene-Awar...
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07/20/2020
Frustratingly Hard Evidence Retrieval for QA Over Books
A lot of progress has been made to improve question answering (QA) in re...
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05/09/2020
Diversifying Dialogue Generation with Non-Conversational Text
Neural network-based sequence-to-sequence (seq2seq) models strongly suff...
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05/03/2020
Neural Data-to-Text Generation via Jointly Learning the Segmentation and Correspondence
The neural attention model has achieved great success in data-to-text ge...
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01/17/2020
Trust in AutoML: Exploring Information Needs for Establishing Trust in Automated Machine Learning Systems
We explore trust in a relatively new area of data science: Automated Mac...
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09/10/2019
Select and Attend: Towards Controllable Content Selection in Text Generation
Many text generation tasks naturally contain two steps: content selectio...
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06/14/2019
Improving Multi-turn Dialogue Modelling with Utterance ReWriter
Recent research has made impressive progress in single-turn dialogue mod...
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10/27/2018
Reagent: Converting Ordinary Webpages into Interactive Software Agents
We introduce Reagent, a technology that readily converts ordinary webpag...
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09/27/2018
NEXUS Network: Connecting the Preceding and the Following in Dialogue Generation
Sequence-to-Sequence (seq2seq) models have become overwhelmingly popular...
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05/14/2018
A Cost-Effective Framework for Preference Elicitation and Aggregation
We propose a cost-effective framework for preference elicitation and agg...
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02/06/2018
Improving Variational Encoder-Decoders in Dialogue Generation
Variational encoder-decoders (VEDs) have shown promising results in dial...
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10/11/2017
DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
We develop a high-quality multi-turn dialog dataset, DailyDialog, which ...
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09/14/2017
Towards Cognitive-and-Immersive Systems: Experiments in a Shared (or common) Blockworld Framework
As computational power has continued to increase, and sensors have becom...
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04/30/2017
