2.2k citations · 10.9k across the 144 of their papers we have counts for
17 papers · 1 filter
A User Simulator for Task-Completion Dialogues
Xiujun Li, Zachary C. Lipton, Bhuwan Dhingra +3
Despite widespread interests in reinforcement-learning for task-oriented dialogue systems, several obstacles can frustrate research and development progress. First, reinforcement l…
MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
Payal Bajaj, Daniel Campos, Nick Craswell +12
We introduce a large scale MAchine Reading COmprehension dataset, which we name MS MARCO. The dataset comprises of 1,010,916 anonymized questions---sampled from Bing's search query…
Semantic Compositional Networks for Visual Captioning
Zhe Gan, Chuang Gan, Xiaodong He +5
A Semantic Compositional Network (SCN) is developed for image captioning, in which semantic concepts (i.e., tags) are detected from the image, and the probability of each tag is us…
Link Prediction using Embedded Knowledge Graphs
Yelong Shen, Po-Sen Huang, Ming-Wei Chang +1
Since large knowledge bases are typically incomplete, missing facts need to be inferred from observed facts in a task called knowledge base completion. The most successful approach…
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency
Adji B. Dieng, Chong Wang, Jianfeng Gao +1
In this paper, we propose TopicRNN, a recurrent neural network (RNN)-based language model designed to directly capture the global semantic meaning relating words in a document via…
Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear
Zachary C. Lipton, Kamyar Azizzadenesheli, Abhishek Kumar +3
Many practical environments contain catastrophic states that an optimal agent would visit infrequently or never. Even on toy problems, Deep Reinforcement Learning (DRL) agents tend…
Bi-directional Attention with Agreement for Dependency Parsing
Hao Cheng, Hao Fang, Xiaodong He +2
We develop a novel bi-directional attention model for dependency parsing, which learns to agree on headword predictions from the forward and backward parsing directions. The parsin…
Knowledge as a Teacher: Knowledge-Guided Structural Attention Networks
Yun-Nung Chen, Dilek Hakkani-Tur, Gokhan Tur +3
Natural language understanding (NLU) is a core component of a spoken dialogue system. Recently recurrent neural networks (RNN) obtained strong results on NLU due to their superior…
ReasoNet: Learning to Stop Reading in Machine Comprehension
Yelong Shen, Po-Sen Huang, Jianfeng Gao +1
Teaching a computer to read and answer general questions pertaining to a document is a challenging yet unsolved problem. In this paper, we describe a novel neural network architect…
Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access
Bhuwan Dhingra, Lihong Li, Xiujun Li +4
This paper proposes KB-InfoBot -- a multi-turn dialogue agent which helps users search Knowledge Bases (KBs) without composing complicated queries. Such goal-oriented dialogue agen…
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems
Zachary C. Lipton, Xiujun Li, Jianfeng Gao +3
We present a new algorithm that significantly improves the efficiency of exploration for deep Q-learning agents in dialogue systems. Our agents explore via Thompson sampling, drawi…
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
Yandong Guo, Lei Zhang, Yuxiao Hu +2
In this paper, we design a benchmark task and provide the associated datasets for recognizing face images and link them to corresponding entity keys in a knowledge base. More speci…
Unsupervised Learning of Predictors from Unpaired Input-Output Samples
Jianshu Chen, Po-Sen Huang, Xiaodong He +2
Unsupervised learning is the most challenging problem in machine learning and especially in deep learning. Among many scenarios, we study an unsupervised learning problem of high e…
Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads
Ji He, Mari Ostendorf, Xiaodong He +4
We introduce an online popularity prediction and tracking task as a benchmark task for reinforcement learning with a combinatorial, natural language action space. A specified numbe…
Deep Reinforcement Learning for Dialogue Generation
Jiwei Li, Will Monroe, Alan Ritter +3
Recent neural models of dialogue generation offer great promise for generating responses for conversational agents, but tend to be shortsighted, predicting utterances one at a time…
A Persona-Based Neural Conversation Model
Jiwei Li, Michel Galley, Chris Brockett +3
We present persona-based models for handling the issue of speaker consistency in neural response generation. A speaker model encodes personas in distributed embeddings that capture…
Basic Reasoning with Tensor Product Representations
Paul Smolensky, Moontae Lee, Xiaodong He +3
In this paper we present the initial development of a general theory for mapping inference in predicate logic to computation over Tensor Product Representations (TPRs; Smolensky (1…