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Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge
In this paper, we aim to extract commonsense knowledge to improve machin...
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Comprehensive Image Captioning via Scene Graph Decomposition
We address the challenging problem of image captioning by revisiting the...
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On Effective Parallelization of Monte Carlo Tree Search
Despite its groundbreaking success in Go and computer games, Monte Carlo...
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Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension
In this paper, we study machine reading comprehension (MRC) on long text...
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Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehensio
In this paper, we study machine reading comprehension (MRC) on long text...
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Logical Natural Language Generation from Open-Domain Tables
Neural natural language generation (NLG) models have recently shown rema...
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Teaching Pretrained Models with Commonsense Reasoning: A Preliminary KB-Based Approach
Recently, pretrained language models (e.g., BERT) have achieved great su...
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TabFact: A Large-scale Dataset for Table-based Fact Verification
The problem of verifying whether a textual hypothesis holds the truth ba...
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Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization
We consider a generic empirical composition optimization problem, where ...
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From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation
Many important classification problems, such as object classification, s...
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Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention
Semantically controlled neural response generation on limited-domain has...
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Evidence Sentence Extraction for Machine Reading Comprehension
Recently remarkable success has been achieved in machine reading compreh...
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DREAM: A Challenge Dataset and Models for Dialogue-Based Reading Comprehension
We present DREAM, the first dialogue-based multiple-choice reading compr...
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Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching
We consider the problem of training speech recognition systems without u...
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Incorporating Structured Commonsense Knowledge in Story Completion
The ability to select an appropriate story ending is the first step towa...
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P-MCGS: Parallel Monte Carlo Acyclic Graph Search
Recently, there have been great interests in Monte Carlo Tree Search (MC...
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XL-NBT: A Cross-lingual Neural Belief Tracking Framework
Task-oriented dialog systems are becoming pervasive, and many companies ...
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ReinforceWalk: Learning to Walk in Graph with Monte Carlo Tree Search
Learning to walk over a graph towards a target node for a given input qu...
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Smoothed Dual Embedding Control
We revisit the Bellman optimality equation with Nesterov's smoothing tec...
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A Learning-to-Infer Method for Real-Time Power Grid Topology Identification
Identifying arbitrary topologies of power networks in real time is a com...
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Stochastic Variance Reduction Methods for Policy Evaluation
Policy evaluation is a crucial step in many reinforcement-learning proce...
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Character-level Deep Conflation for Business Data Analytics
Connecting different text attributes associated with the same entity (co...
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Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads
We introduce an online popularity prediction and tracking task as a benc...
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Deep Reinforcement Learning with a Natural Language Action Space
This paper introduces a novel architecture for reinforcement learning wi...
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Recurrent Reinforcement Learning: A Hybrid Approach
Successful applications of reinforcement learning in real-world problems...
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Deep Sentence Embedding Using Long Short-Term Memory Networks: Analysis and Application to Information Retrieval
This paper develops a model that addresses sentence embedding, a hot top...
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Distributed Policy Evaluation Under Multiple Behavior Strategies
We apply diffusion strategies to develop a fully-distributed cooperative...
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A Primal-Dual Method for Training Recurrent Neural Networks Constrained by the Echo-State Property
We present an architecture of a recurrent neural network (RNN) with a fu...
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