Jianshu Chen

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Microsoft

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Tencent

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The Regents of the University of California

Currently a principal researcher at Tencent AI Lab, working on machine learning and natural language processing. Worked in the Deep Learning Technology Center (DLTC) at Microsoft Research, Redmond, WA. Completed my PhD in Electrical Engineering at University of California, Los Angeles (UCLA).

Featured Co-authors

Xin Wang
304 publications
H. Vincent Poor
287 publications
Jianfeng Gao
208 publications
Bo Liu
134 publications
Yu Liu
133 publications
Liwei Wang
128 publications
William Yang Wang
125 publications
Dong Yu
125 publications
Ji Liu
124 publications
Dan Roth
111 publications
Zhou Yu
101 publications

∙ 09/07/2022

Blessing of Class Diversity in Pre-training

This paper presents a new statistical analysis aiming to explain the rec...

Yulai Zhao, et al. ∙

∙ 03/19/2022

Learning-by-Narrating: Narrative Pre-Training for Zero-Shot Dialogue Comprehension

Comprehending a dialogue requires a model to capture diverse kinds of ke...

Chao Zhao, et al. ∙

∙ 03/16/2022

C-MORE: Pretraining to Answer Open-Domain Questions by Consulting Millions of References

We consider the problem of pretraining a two-stage open-domain question ...

Xiang Yue, et al. ∙

∙ 02/01/2022

Planner-Reasoner Inside a Multi-task Reasoning Agent

We consider the problem of multi-task reasoning (MTR), where an agent ca...

Daoming Lyu, et al. ∙

∙ 10/27/2021

Connect-the-Dots: Bridging Semantics between Words and Definitions via Aligning Word Sense Inventories

Word Sense Disambiguation (WSD) aims to automatically identify the exact...

Wenlin Yao, et al. ∙

∙ 09/12/2020

Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge

In this paper, we aim to extract commonsense knowledge to improve machin...

Kai Sun, et al. ∙

∙ 07/23/2020

Comprehensive Image Captioning via Scene Graph Decomposition

We address the challenging problem of image captioning by revisiting the...

Yiwu Zhong, et al. ∙

∙ 06/15/2020

On Effective Parallelization of Monte Carlo Tree Search

Despite its groundbreaking success in Go and computer games, Monte Carlo...

Anji Liu, et al. ∙

∙ 05/16/2020

Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension

In this paper, we study machine reading comprehension (MRC) on long text...

Hongyu Gong, et al. ∙

∙ 05/16/2020

Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehensio

In this paper, we study machine reading comprehension (MRC) on long text...

Hongyu Gong, et al. ∙

∙ 04/22/2020

Logical Natural Language Generation from Open-Domain Tables

Neural natural language generation (NLG) models have recently shown rema...

Wenhu Chen, et al. ∙

∙ 09/20/2019

Teaching Pretrained Models with Commonsense Reasoning: A Preliminary KB-Based Approach

Recently, pretrained language models (e.g., BERT) have achieved great su...

Shiyang Li, et al. ∙

∙ 09/05/2019

TabFact: A Large-scale Dataset for Table-based Fact Verification

The problem of verifying whether a textual hypothesis holds the truth ba...

Wenhu Chen, et al. ∙

∙ 07/22/2019

Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization

We consider a generic empirical composition optimization problem, where ...

Adithya M. Devraj, et al. ∙

∙ 06/06/2019

From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation

Many important classification problems, such as object classification, s...

Yu Liu, et al. ∙

∙ 05/30/2019

Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention

Semantically controlled neural response generation on limited-domain has...

Wenhu Chen, et al. ∙

∙ 02/23/2019

Evidence Sentence Extraction for Machine Reading Comprehension

Recently remarkable success has been achieved in machine reading compreh...

Hai Wang, et al. ∙

∙ 02/01/2019

DREAM: A Challenge Dataset and Models for Dialogue-Based Reading Comprehension

We present DREAM, the first dialogue-based multiple-choice reading compr...

Kai Sun, et al. ∙

∙ 12/23/2018

Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching

We consider the problem of training speech recognition systems without u...

Chih-Kuan Yeh, et al. ∙

∙ 11/01/2018

Incorporating Structured Commonsense Knowledge in Story Completion

The ability to select an appropriate story ending is the first step towa...

Jiaao Chen, et al. ∙

∙ 10/28/2018

P-MCGS: Parallel Monte Carlo Acyclic Graph Search

Recently, there have been great interests in Monte Carlo Tree Search (MC...

Chen Yu, et al. ∙

∙ 08/19/2018

XL-NBT: A Cross-lingual Neural Belief Tracking Framework

Task-oriented dialog systems are becoming pervasive, and many companies ...

Wenhu Chen, et al. ∙

∙ 02/12/2018

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...

Yelong Shen, et al. ∙

∙ 12/29/2017

Smoothed Dual Embedding Control

We revisit the Bellman optimality equation with Nesterov's smoothing tec...

Bo Dai, et al. ∙

∙ 10/21/2017

A Learning-to-Infer Method for Real-Time Power Grid Topology Identification

Identifying arbitrary topologies of power networks in real time is a com...

Yue Zhao, et al. ∙

∙ 02/25/2017

Stochastic Variance Reduction Methods for Policy Evaluation

Policy evaluation is a crucial step in many reinforcement-learning proce...

Simon S. Du, et al. ∙

∙ 02/08/2017

Character-level Deep Conflation for Business Data Analytics

Connecting different text attributes associated with the same entity (co...

Zhe Gan, et al. ∙

∙ 06/12/2016

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...

Ji He, et al. ∙

∙ 11/14/2015

Deep Reinforcement Learning with a Natural Language Action Space

This paper introduces a novel architecture for reinforcement learning wi...

Ji He, et al. ∙

∙ 09/10/2015

Recurrent Reinforcement Learning: A Hybrid Approach

Successful applications of reinforcement learning in real-world problems...

Xiujun Li, et al. ∙

∙ 02/24/2015

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...

Hamid Palangi, et al. ∙

∙ 12/30/2013

Distributed Policy Evaluation Under Multiple Behavior Strategies

We apply diffusion strategies to develop a fully-distributed cooperative...

Sergio Valcarcel Macua, et al. ∙

∙ 11/24/2013

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...

Jianshu Chen, et al. ∙