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WSL-DS: Weakly Supervised Learning with Distant Supervision for Query Focused Multi-Document Abstractive Summarization
MdTahmidRahmanLaskar, EnamulHoque, JimmyXiangjiHuang....
Published date-11/03/2020
AbstractiveTextSummarization, DocumentSummarization, Multi-DocumentSummarization
In the Query Focused Multi-Document Summarization (QF-MDS) task, a set of documents and a query are given where the goal is to generate a summary from these documents based on …
Semi-Supervised Cleansing of Web Argument Corpora
JonasDorsch, HenningWachsmuth....
Published date-11/03/2020
Debate portals and similar web platforms constitute one of the main text sources in computational argumentation research and its applications. While the corpora built upon these sources are rich of …
Meta-Learning for Natural Language Understanding under Continual Learning Framework
JiachengWang, YongFan, DuoJiang....
Published date-11/03/2020
ContinualLearning, Meta-Learning, NaturalLanguageUnderstanding
Neural network has been recognized with its accomplishments on tackling various natural language understanding (NLU) tasks. Methods have been developed to train a robust model to handle multiple tasks to …
MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks
AshishKumar, KaranSehgal, PrernaGarg....
Published date-11/03/2020
ImageClassification
Deep convolutional networks have been quite successful at various image classification tasks. The current methods to explain the predictions of a pre-trained model rely on gradient information, often resulting in …
Intrinsic Robotic Introspection: Learning Internal States From Neuron Activations
NikosPitsillos, AmeyaPore, BjornSandJensen....
Published date-11/03/2020
We present an introspective framework inspired by the process of how humans perform introspection. Our working assumption is that neural network activations encode information, and building internal states from these …
Parameter Efficient Deep Neural Networks with Bilinear Projections
LitaoYu, YongshengGao, JunZhou....
Published date-11/03/2020
Recent research on deep neural networks (DNNs) has primarily focused on improving the model accuracy. Given a proper deep learning framework, it is generally possible to increase the depth or …