b'Xiaoxiao Guo'

research

∙ 06/07/2021

Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study

Recent advancements in open-domain question answering (ODQA), i.e., find...

0 Xiangyang Mou, et al. ∙

research

∙ 12/23/2020

Augmenting Policy Learning with Routines Discovered from a Single Demonstration

Humans can abstract prior knowledge from very little data and use it to ...

6 Zelin Zhao, et al. ∙

research

∙ 10/19/2020

Deriving Commonsense Inference Tasks from Interactive Fictions

Commonsense reasoning simulates the human ability to make presumptions a...

0 Mo Yu, et al. ∙

research

∙ 10/05/2020

Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement Learning

Interactive Fiction (IF) games with real human-written natural language ...

4 Xiaoxiao Guo, et al. ∙

research

∙ 07/20/2020

Frustratingly Hard Evidence Retrieval for QA Over Books

A lot of progress has been made to improve question answering (QA) in re...

0 Xiangyang Mou, et al. ∙

research

∙ 04/06/2020

Learning to Recover Reasoning Chains for Multi-Hop Question Answering via Cooperative Games

We propose the new problem of learning to recover reasoning chains from ...

0 Yufei Feng, et al. ∙

research

∙ 11/10/2019

Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries

This paper explores the task of interactive image retrieval using natura...

19 Fuwen Tan, et al. ∙

research

∙ 10/31/2019

Do Multi-hop Readers Dream of Reasoning Chains?

General Question Answering (QA) systems over texts require the multi-hop...

0 Haoyu Wang, et al. ∙

research

∙ 09/17/2019

Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering

Multi-hop question answering (QA) requires an information retrieval (IR)...

0 Ameya Godbole, et al. ∙

research

∙ 09/17/2019

Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering

A key challenge of multi-hop question answering (QA) in the open-domain ...

0 Wenhan Xiong, et al. ∙

research

∙ 08/13/2019

Meta Reasoning over Knowledge Graphs

The ability to reason over learned knowledge is an innate ability for hu...

0 Hong Wang, et al. ∙

research

∙ 08/07/2019

Attend To Count: Crowd Counting with Adaptive Capacity Multi-scale CNNs

Crowd counting is a challenging task due to the large variations in crow...

4 Zhikang Zou, et al. ∙

research

∙ 07/14/2019

TWEETQA: A Social Media Focused Question Answering Dataset

With social media becoming increasingly pop-ular on which lots of news a...

0 Wenhan Xiong, et al. ∙

research

∙ 06/11/2019

Self-Supervised Learning for Contextualized Extractive Summarization

Existing models for extractive summarization are usually trained from sc...

0 Hong Wang, et al. ∙

research

∙ 05/30/2019

The Fashion IQ Dataset: Retrieving Images by Combining Side Information and Relative Natural Language Feedback

We contribute a new dataset and a novel method for natural language base...

0 Xiaoxiao Guo, et al. ∙

research

∙ 05/17/2019

Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader

We propose a new end-to-end question answering model, which learns to ag...

5 Wenhan Xiong, et al. ∙

research

∙ 04/04/2019

A Hybrid Approach with Optimization and Metric-based Meta-Learner for Few-Shot Learning

Few-shot learning aims to learn classifiers for new classes with only a ...

0 Duo Wang, et al. ∙

research

∙ 03/11/2019

Hybrid Reinforcement Learning with Expert State Sequences

Existing imitation learning approaches often require that the complete d...

8 Xiaoxiao Guo, et al. ∙

research

∙ 03/06/2019

Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing

Existing entity typing systems usually exploit the type hierarchy provid...

0 Wenhan Xiong, et al. ∙

research

∙ 03/06/2019

Sentence Embedding Alignment for Lifelong Relation Extraction

Conventional approaches to relation extraction usually require a fixed s...

0 Hong Wang, et al. ∙

research

∙ 02/04/2019

Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers

Most approaches to extraction multiple relations from a paragraph requir...

4 Haoyu Wang, et al. ∙

research

∙ 01/26/2019

Few-shot Learning with Meta Metric Learners

Few-shot Learning aims to learn classifiers for new classes with only a ...

8 Yu Cheng, et al. ∙

research

∙ 08/27/2018

One-Shot Relational Learning for Knowledge Graphs

Knowledge graphs (KGs) are the key components of various natural languag...

0 Wenhan Xiong, et al. ∙

research

∙ 06/16/2018

Scheduled Policy Optimization for Natural Language Communication with Intelligent Agents

We investigate the task of learning to follow natural language instructi...

0 Wenhan Xiong, et al. ∙

research

∙ 05/19/2018

Diverse Few-Shot Text Classification with Multiple Metrics

We study few-shot learning in natural language domains. Compared to many...

0 Mo Yu, et al. ∙

research

∙ 05/01/2018

Dialog-based Interactive Image Retrieval

Existing methods for interactive image retrieval have demonstrated the m...

0 Xiaoxiao Guo, et al. ∙

research

∙ 04/22/2018

Named Entities troubling your Neural Methods? Build NE-Table: A neural approach for handling Named Entities

Many natural language processing tasks require dealing with Named Entiti...

0 Janarthanan Rajendran, et al. ∙

research

∙ 11/14/2017

Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering

A popular recent approach to answering open-domain questions is to first...

0 Shuohang Wang, et al. ∙

research

∙ 10/30/2017

Eigenoption Discovery through the Deep Successor Representation

Options in reinforcement learning allow agents to hierarchically decompo...

0 Marlos C. Machado, et al. ∙

research

∙ 10/05/2017

Dilated Recurrent Neural Networks

Learning with recurrent neural networks (RNNs) on long sequences is a no...

0 Shiyu Chang, et al. ∙

research

∙ 08/31/2017

R^3: Reinforced Reader-Ranker for Open-Domain Question Answering

In recent years researchers have achieved considerable success applying ...

0 Shuohang Wang, et al. ∙

research

∙ 08/26/2017

Robust Task Clustering for Deep Many-Task Learning

We investigate task clustering for deep-learning based multi-task and fe...

0 Mo Yu, et al. ∙

research

∙ 01/16/2017

Deep Memory Networks for Attitude Identification

We consider the task of identifying attitudes towards a given set of ent...

0 Cheng Li, et al. ∙

research

∙ 07/31/2015

Action-Conditional Video Prediction using Deep Networks in Atari Games

Motivated by vision-based reinforcement learning (RL) problems, in parti...

0 Junhyuk Oh, et al. ∙

Xiaoxiao Guo

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