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Filtering before Iteratively Referring for Knowledge-Grounded Response Selection in Retrieval-Based Chatbots
The challenges of building knowledge-grounded retrieval-based chatbots l...
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DialBERT: A Hierarchical Pre-Trained Model for Conversation Disentanglement
Disentanglement is a problem in which multiple conversations occur in th...
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Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots
In this paper, we study the problem of employing pre-trained language mo...
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Several Experiments on Investigating Pretraining and Knowledge-Enhanced Models for Natural Language Inference
Natural language inference (NLI) is among the most challenging tasks in ...
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Exploring Unsupervised Pretraining and Sentence Structure Modelling for Winograd Schema Challenge
Winograd Schema Challenge (WSC) was proposed as an AI-hard problem in te...
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Spelling Error Correction Using a Nested RNN Model and Pseudo Training Data
We propose a nested recurrent neural network (nested RNN) model for Engl...
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Natural Language Inference with External Knowledge
Modeling informal inference in natural language is very challenging. Wit...
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Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference
The RepEval 2017 Shared Task aims to evaluate natural language understan...
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Exploring Question Understanding and Adaptation in Neural-Network-Based Question Answering
The last several years have seen intensive interest in exploring neural-...
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Commonsense Knowledge Enhanced Embeddings for Solving Pronoun Disambiguation Problems in Winograd Schema Challenge
In this paper, we propose commonsense knowledge enhanced embeddings (KEE...
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Neural Networks Models for Entity Discovery and Linking
This paper describes the USTC_NELSLIP systems submitted to the Trilingua...
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Distraction-Based Neural Networks for Document Summarization
Distributed representation learned with neural networks has recently sho...
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Attention-over-Attention Neural Networks for Reading Comprehension
Cloze-style queries are representative problems in reading comprehension...
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Probabilistic Reasoning via Deep Learning: Neural Association Models
In this paper, we propose a new deep learning approach, called neural as...
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Feedforward Sequential Memory Networks: A New Structure to Learn Long-term Dependency
In this paper, we propose a novel neural network structure, namely feedf...
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Feedforward Sequential Memory Neural Networks without Recurrent Feedback
We introduce a new structure for memory neural networks, called feedforw...
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