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Multi-Domain Joint Semantic Frame Parsing Using Bi-Directional RNN-LSTM
TLDR
This paper proposes a holistic multi-domain, multi-task (i.e. slot filling, domain and intent detection) modeling approach to estimate complete semantic frames for all user utterances addressed to a conversational system, demonstrating the distinctive power of deep learning methods, namely bi-directional recurrent neural network (RNN) with long-short term memory (LSTM) cells to handle such complexity. Expand
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Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation
TLDR
We propose a novel Reinforced Cross-Modal Matching (RCM) approach that enforces cross-modal grounding both locally and globally via reinforcement learning (RL). Expand
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COMET: Commonsense Transformers for Automatic Knowledge Graph Construction
TLDR
We present the first comprehensive study on automatic knowledge base construction for two prevalent commonsense knowledge graphs: ATOMIC (Sap et al., 2019) and ConceptNet. Expand
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Deep Communicating Agents for Abstractive Summarization
TLDR
We present deep communicating agents in an encoder-decoder architecture to address the challenges of representing a long document for abstractive summarization. Expand
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Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing
TLDR
We study different scheduling schemes for 𝛽, and show that KL vanishing is caused by the lack of good latent codes in training decoder at the beginning of optimization. Expand
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A Hybrid Hierarchical Model for Multi-Document Summarization
TLDR
We formulate extractive summarization as a two step learning problem building a generative model for pattern discovery and a regression model for inference. Expand
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End-to-End Task-Completion Neural Dialogue Systems
TLDR
This paper presents a novel end-to-end learning framework for task-completion dialogue systems to tackle such issues. Expand
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Modeling Uncertainty with Fuzzy Logic - With Recent Theory and Applications
TLDR
The objective of this book is to present an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". Expand
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Composite Task-Completion Dialogue Policy Learning via Hierarchical Deep Reinforcement Learning
TLDR
This paper addresses this challenge by formulating the task in the mathematical framework of options over Markov Decision Processes (MDPs), proposing a hierarchical deep reinforcement learning approach to learning a dialogue manager that operates at different temporal scales. Expand
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Discovery of Topically Coherent Sentences for Extractive Summarization
TLDR
We present an unsupervised probabilistic approach to model the hidden abstract concepts across documents as well as the correlation between these concepts, to generate topically coherent and non-redundant summaries. Expand
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