2.2k citations · 10.9k across the 144 of their papers we have counts for
20 papers · 1 filter
The Design and Implementation of XiaoIce, an Empathetic Social Chatbot
Li Zhou, Jianfeng Gao, Di Li +1
This paper describes the development of Microsoft XiaoIce, the most popular social chatbot in the world. XiaoIce is uniquely designed as an AI companion with an emotional connectio…
Sequential Attention GAN for Interactive Image Editing
Yu Cheng, Zhe Gan, Yitong Li +2
Most existing text-to-image synthesis tasks are static single-turn generation, based on pre-defined textual descriptions of images. To explore more practical and interactive real-l…
StoryGAN: A Sequential Conditional GAN for Story Visualization
Yitong Li, Zhe Gan, Yelong Shen +6
We propose a new task, called Story Visualization. Given a multi-sentence paragraph, the story is visualized by generating a sequence of images, one for each sentence. In contrast…
Switch-based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning
Yuexin Wu, Xiujun Li, Jingjing Liu +2
Training task-completion dialogue agents with reinforcement learning usually requires a large number of real user experiences. The Dyna-Q algorithm extends Q-learning by integratin…
Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation
Xin Wang, Qiuyuan Huang, Asli Celikyilmaz +5
Vision-language navigation (VLN) is the task of navigating an embodied agent to carry out natural language instructions inside real 3D environments. In this paper, we study how to…
Towards Coherent and Cohesive Long-form Text Generation
Woon Sang Cho, Pengchuan Zhang, Yizhe Zhang +5
Generating coherent and cohesive long-form texts is a challenging task. Previous works relied on large amounts of human-generated texts to train neural language models. However, fe…
ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension
Sheng Zhang, Xiaodong Liu, Jingjing Liu +3
We present a large-scale dataset, ReCoRD, for machine reading comprehension requiring commonsense reasoning. Experiments on this dataset demonstrate that the performance of state-o…
Stochastic Answer Networks for SQuAD 2.0
Xiaodong Liu, Wei Li, Yuwei Fang +3
This paper presents an extension of the Stochastic Answer Network (SAN), one of the state-of-the-art machine reading comprehension models, to be able to judge whether a question is…
Discriminative Deep Dyna-Q: Robust Planning for Dialogue Policy Learning
Shang-Yu Su, Xiujun Li, Jianfeng Gao +2
This paper presents a Discriminative Deep Dyna-Q (D3Q) approach to improving the effectiveness and robustness of Deep Dyna-Q (DDQ), a recently proposed framework that extends the D…
Multi-task Learning with Sample Re-weighting for Machine Reading Comprehension
Yichong Xu, Xiaodong Liu, Yelong Shen +2
We propose a multi-task learning framework to learn a joint Machine Reading Comprehension (MRC) model that can be applied to a wide range of MRC tasks in different domains. Inspire…
Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization
Yizhe Zhang, Michel Galley, Jianfeng Gao +4
Responses generated by neural conversational models tend to lack informativeness and diversity. We present Adversarial Information Maximization (AIM), an adversarial learning strat…
Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning
Ziyu Yao, Xiujun Li, Jianfeng Gao +2
Given a text description, most existing semantic parsers synthesize a program in one shot. However, it is quite challenging to produce a correct program solely based on the descrip…
Microsoft Dialogue Challenge: Building End-to-End Task-Completion Dialogue Systems
Xiujun Li, Yu Wang, Siqi Sun +3
This proposal introduces a Dialogue Challenge for building end-to-end task-completion dialogue systems, with the goal of encouraging the dialogue research community to collaborate…
The Neural Painter: Multi-Turn Image Generation
Ryan Y. Benmalek, Claire Cardie, Serge Belongie +2
In this work we combine two research threads from Vision/ Graphics and Natural Language Processing to formulate an image generation task conditioned on attributes in a multi-turn s…
Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models
Minjia Zhang, Xiaodong Liu, Wenhan Wang +2
Neural language models (NLMs) have recently gained a renewed interest by achieving state-of-the-art performance across many natural language processing (NLP) tasks. However, NLMs a…
Discourse-Aware Neural Rewards for Coherent Text Generation
Antoine Bosselut, Asli Celikyilmaz, Xiaodong He +3
In this paper, we investigate the use of discourse-aware rewards with reinforcement learning to guide a model to generate long, coherent text. In particular, we propose to learn ne…
Stochastic Answer Networks for Natural Language Inference
Xiaodong Liu, Kevin Duh, Jianfeng Gao
We propose a stochastic answer network (SAN) to explore multi-step inference strategies in Natural Language Inference. Rather than directly predicting the results given the inputs,…
Subgoal Discovery for Hierarchical Dialogue Policy Learning
Da Tang, Xiujun Li, Jianfeng Gao +3
Developing agents to engage in complex goal-oriented dialogues is challenging partly because the main learning signals are very sparse in long conversations. In this paper, we prop…
M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search
Yelong Shen, Jianshu Chen, Po-Sen Huang +2
Learning to walk over a graph towards a target node for a given query and a source node is an important problem in applications such as knowledge base completion (KBC). It can be f…
Deep Dyna-Q: Integrating Planning for Task-Completion Dialogue Policy Learning
Baolin Peng, Xiujun Li, Jianfeng Gao +3
Training a task-completion dialogue agent via reinforcement learning (RL) is costly because it requires many interactions with real users. One common alternative is to use a user s…