Search Results for author: Ting Liu

Found 257 papers, 92 papers with code

Technical Report on Shared Task in DialDoc21

no code implementations ACL (dialdoc) 2021 Jiapeng Li, Mingda Li, Longxuan Ma, Wei-Nan Zhang, Ting Liu

The task requires identifying the grounding knowledge in form of a document span for the next dialogue turn.

Data Augmentation

Neural Natural Logic Inference for Interpretable Question Answering

1 code implementation EMNLP 2021 Jihao Shi, Xiao Ding, Li Du, Ting Liu, Bing Qin

Many open-domain question answering problems can be cast as a textual entailment task, where a question and candidate answers are concatenated to form hypotheses.

Natural Language Inference Open-Domain Question Answering

Weakly Supervised Semantic Parsing by Learning from Mistakes

1 code implementation Findings (EMNLP) 2021 Jiaqi Guo, Jian-Guang Lou, Ting Liu, Dongmei Zhang

Using only 10% of utterance-denotation pairs, the parser achieves 84. 2 denotation accuracy on WikiSQL, which is competitive with the previous state-of-the-art approaches using 100% labeled data.

Semantic Parsing

Counterfactual Off-Policy Training for Neural Dialogue Generation

no code implementations EMNLP 2020 Qingfu Zhu, Wei-Nan Zhang, Ting Liu, William Yang Wang

Open-domain dialogue generation suffers from the data insufficiency problem due to the vast size of potential responses.

Dialogue Generation

A Semantic Web Technology Index

no code implementations14 Jan 2022 Gongjin Lan, Ting Liu, Xu Wang, Xueli Pan, Zhisheng Huang

In this paper, we propose an SW technology index to standardize the development for ensuring that the work of SW technology is designed well and to quantitatively evaluate the quality of the work in SW technology.

Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving

no code implementations22 Dec 2021 Jingxiao Zheng, Xinwei Shi, Alexander Gorban, Junhua Mao, Yang song, Charles R. Qi, Ting Liu, Visesh Chari, Andre Cornman, Yin Zhou, CongCong Li, Dragomir Anguelov

3D human pose estimation (HPE) in autonomous vehicles (AV) differs from other use cases in many factors, including the 3D resolution and range of data, absence of dense depth maps, failure modes for LiDAR, relative location between the camera and LiDAR, and a high bar for estimation accuracy.

3D Human Pose Estimation Autonomous Driving

Contextualized Spatio-Temporal Contrastive Learning with Self-Supervision

no code implementations9 Dec 2021 Liangzhe Yuan, Rui Qian, Yin Cui, Boqing Gong, Florian Schroff, Ming-Hsuan Yang, Hartwig Adam, Ting Liu

We first design a region-based self-supervised pretext task which requires the model to learn to transform instance representations from one view to another guided by context features.

Action Recognition Contrastive Learning +3

Exploring Temporal Granularity in Self-Supervised Video Representation Learning

no code implementations8 Dec 2021 Rui Qian, Yeqing Li, Liangzhe Yuan, Boqing Gong, Ting Liu, Matthew Brown, Serge Belongie, Ming-Hsuan Yang, Hartwig Adam, Yin Cui

The training objective consists of two parts: a fine-grained temporal learning objective to maximize the similarity between corresponding temporal embeddings in the short clip and the long clip, and a persistent temporal learning objective to pull together global embeddings of the two clips.

Representation Learning Self-Supervised Learning

One to Multiple Mapping Dual Learning: Learning Multiple Sources from One Mixed Signal

no code implementations13 Oct 2021 Ting Liu, Wenwu Wang, Xiaofei Zhang, Zhenyin Gong, Yina Guo

Single channel blind source separation (SCBSS) refers to separate multiple sources from a mixed signal collected by a single sensor.

Less is More: Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification

1 code implementation22 Sep 2021 Suncheng Xiang, Guanjie You, Mengyuan Guan, Hao Chen, Binjie Yan, Ting Liu, Yuzhuo Fu

Moreover, aiming to fully exploit the potential of FineGPR and promote the efficient training from millions of synthetic data, we propose an attribute analysis pipeline called AOST, which dynamically learns attribute distribution in real domain, then eliminates the gap between synthetic and real-world data and thus is freely deployed to new scenarios.

Person Re-Identification Style Transfer

Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training

1 code implementation EMNLP 2021 Bo Zheng, Li Dong, Shaohan Huang, Saksham Singhal, Wanxiang Che, Ting Liu, Xia Song, Furu Wei

We find that many languages are under-represented in recent cross-lingual language models due to the limited vocabulary capacity.

Language Modelling

Logic-level Evidence Retrieval and Graph-based Verification Network for Table-based Fact Verification

1 code implementation EMNLP 2021 Qi Shi, Yu Zhang, Qingyu Yin, Ting Liu

Specifically, we first retrieve logic-level program-like evidence from the given table and statement as supplementary evidence for the table.

Fact Verification Table-based Fact Verification

Understanding Attention in Machine Reading Comprehension

no code implementations26 Aug 2021 Yiming Cui, Wei-Nan Zhang, Wanxiang Che, Ting Liu, Zhigang Chen

Achieving human-level performance on some of Machine Reading Comprehension (MRC) datasets is no longer challenging with the help of powerful Pre-trained Language Models (PLMs).

Machine Reading Comprehension Span-Extraction MRC

Neural Stylistic Response Generation with Disentangled Latent Variables

no code implementations ACL 2021 Qingfu Zhu, Wei-Nan Zhang, Ting Liu, William Yang Wang

Generating open-domain conversational responses in the desired style usually suffers from the lack of parallel data in the style.

Learning Event Graph Knowledge for Abductive Reasoning

1 code implementation ACL 2021 Li Du, Xiao Ding, Ting Liu, Bing Qin

Abductive reasoning aims at inferring the most plausible explanation for observed events, which would play critical roles in various NLP applications, such as reading comprehension and question answering.

Question Answering Reading Comprehension

ExCAR: Event Graph Knowledge Enhanced Explainable Causal Reasoning

no code implementations ACL 2021 Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin

ExCAR first acquires additional evidence information from a large-scale causal event graph as logical rules for causal reasoning.

Representation Learning

Chase: A Large-Scale and Pragmatic Chinese Dataset for Cross-Database Context-Dependent Text-to-SQL

no code implementations ACL 2021 Jiaqi Guo, Ziliang Si, Yu Wang, Qian Liu, Ming Fan, Jian-Guang Lou, Zijiang Yang, Ting Liu

However, we identify two biases in existing datasets for XDTS: (1) a high proportion of context-independent questions and (2) a high proportion of easy SQL queries.

Text-To-Sql

Guided Generation of Cause and Effect

no code implementations21 Jul 2021 Zhongyang Li, Xiao Ding, Ting Liu, J. Edward Hu, Benjamin Van Durme

We present a conditional text generation framework that posits sentential expressions of possible causes and effects.

Conditional Text Generation Knowledge Graphs

CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervision

no code implementations21 Jul 2021 Zhongyang Li, Xiao Ding, Kuo Liao, Bing Qin, Ting Liu

Recent work has shown success in incorporating pre-trained models like BERT to improve NLP systems.

Causal Inference

Non-Convex Tensor Low-Rank Approximation for Infrared Small Target Detection

1 code implementation31 May 2021 Ting Liu, Jungang Yang, Boyang Li, Chao Xiao, Yang Sun, Yingqian Wang, Wei An

Considering that different singular values have different importance and should be treated discriminatively, in this paper, we propose a non-convex tensor low-rank approximation (NTLA) method for infrared small target detection.

Language Model as an Annotator: Exploring DialoGPT for Dialogue Summarization

1 code implementation ACL 2021 Xiachong Feng, Xiaocheng Feng, Libo Qin, Bing Qin, Ting Liu

Current dialogue summarization systems usually encode the text with a number of general semantic features (e. g., keywords and topics) to gain more powerful dialogue modeling capabilities.

Conversational Response Generation Language Modelling

Learning to Bridge Metric Spaces: Few-shot Joint Learning of Intent Detection and Slot Filling

1 code implementation Findings (ACL) 2021 Yutai Hou, Yongkui Lai, Cheng Chen, Wanxiang Che, Ting Liu

However, dialogue language understanding contains two closely related tasks, i. e., intent detection and slot filling, and often benefits from jointly learning the two tasks.

Few-Shot Learning Intent Detection +1

ExpMRC: Explainability Evaluation for Machine Reading Comprehension

1 code implementation10 May 2021 Yiming Cui, Ting Liu, Wanxiang Che, Zhigang Chen, Shijin Wang

Achieving human-level performance on some of Machine Reading Comprehension (MRC) datasets is no longer challenging with the help of powerful Pre-trained Language Models (PLMs).

Machine Reading Comprehension Multi-Choice MRC +1

DADgraph: A Discourse-aware Dialogue Graph Neural Network for Multiparty Dialogue Machine Reading Comprehension

no code implementations26 Apr 2021 Jiaqi Li, Ming Liu, Zihao Zheng, Heng Zhang, Bing Qin, Min-Yen Kan, Ting Liu

Multiparty Dialogue Machine Reading Comprehension (MRC) differs from traditional MRC as models must handle the complex dialogue discourse structure, previously unconsidered in traditional MRC.

Machine Reading Comprehension

Learning to Share by Masking the Non-shared for Multi-domain Sentiment Classification

no code implementations17 Apr 2021 Jianhua Yuan, Yanyan Zhao, Bing Qin, Ting Liu

To this end, we propose the BertMasker network which explicitly masks domain-related words from texts, learns domain-invariant sentiment features from these domain-agnostic texts, and uses those masked words to form domain-aware sentence representations.

General Classification Multi-Domain Sentiment Classification +1

Learning from Self-Discrepancy via Multiple Co-teaching for Cross-Domain Person Re-Identification

1 code implementation6 Apr 2021 Suncheng Xiang, Yuzhuo Fu, Mengyuan Guan, Ting Liu

Employing clustering strategy to assign unlabeled target images with pseudo labels has become a trend for person re-identification (re-ID) algorithms in domain adaptation.

Domain Adaptation Person Re-Identification

A Survey on Spoken Language Understanding: Recent Advances and New Frontiers

1 code implementation4 Mar 2021 Libo Qin, Tianbao Xie, Wanxiang Che, Ting Liu

Spoken Language Understanding (SLU) aims to extract the semantics frame of user queries, which is a core component in a task-oriented dialog system.

Spoken Language Understanding

Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answering

no code implementations7 Feb 2021 Nan Shao, Yiming Cui, Ting Liu, Shijin Wang, Guoping Hu

To deal with this challenge, most of the existing works consider paragraphs as nodes in a graph and propose graph-based methods to retrieve them.

Information Retrieval Multi-hop Question Answering +1

Discovering Dialog Structure Graph for Open-Domain Dialog Generation

no code implementations31 Dec 2020 Jun Xu, Zeyang Lei, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, Ting Liu

Learning interpretable dialog structure from human-human dialogs yields basic insights into the structure of conversation, and also provides background knowledge to facilitate dialog generation.

Open-Domain Dialog

Multiple Structural Priors Guided Self Attention Network for Language Understanding

no code implementations29 Dec 2020 Le Qi, Yu Zhang, Qingyu Yin, Ting Liu

Self attention networks (SANs) have been widely utilized in recent NLP studies.

Co-GAT: A Co-Interactive Graph Attention Network for Joint Dialog Act Recognition and Sentiment Classification

1 code implementation24 Dec 2020 Libo Qin, Zhouyang Li, Wanxiang Che, Minheng Ni, Ting Liu

The dialog context information (contextual information) and the mutual interaction information are two key factors that contribute to the two related tasks.

Graph Attention Sentiment Analysis

C2C-GenDA: Cluster-to-Cluster Generation for Data Augmentation of Slot Filling

1 code implementation13 Dec 2020 Yutai Hou, Sanyuan Chen, Wanxiang Che, Cheng Chen, Ting Liu

Slot filling, a fundamental module of spoken language understanding, often suffers from insufficient quantity and diversity of training data.

Data Augmentation Slot Filling +1

Biomedical Knowledge Graph Refinement with Embedding and Logic Rules

no code implementations2 Dec 2020 Sendong Zhao, Bing Qin, Ting Liu, Fei Wang

This paper proposes a method BioGRER to improve the BioKG's quality, which comprehensively combines the knowledge graph embedding and logic rules that support and negate triplets in the BioKG.

Knowledge Graph Embedding Knowledge Graphs

Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization

1 code implementation CVPR 2021 Long Zhao, Yuxiao Wang, Jiaping Zhao, Liangzhe Yuan, Jennifer J. Sun, Florian Schroff, Hartwig Adam, Xi Peng, Dimitris Metaxas, Ting Liu

To evaluate the power of the learned representations, in addition to the conventional fully-supervised action recognition settings, we introduce a novel task called single-shot cross-view action recognition.

Action Recognition Contrastive Learning +1

TableGPT: Few-shot Table-to-Text Generation with Table Structure Reconstruction and Content Matching

no code implementations COLING 2020 Heng Gong, Yawei Sun, Xiaocheng Feng, Bing Qin, Wei Bi, Xiaojiang Liu, Ting Liu

Although neural table-to-text models have achieved remarkable progress with the help of large-scale datasets, they suffer insufficient learning problem with limited training data.

Few-Shot Learning Language Modelling +2

Unsupervised Explanation Generation for Machine Reading Comprehension

no code implementations13 Nov 2020 Yiming Cui, Ting Liu, Shijin Wang, Guoping Hu

With the blooming of various Pre-trained Language Models (PLMs), Machine Reading Comprehension (MRC) has embraced significant improvements on various benchmarks and even surpass human performances.

Machine Reading Comprehension

CharBERT: Character-aware Pre-trained Language Model

1 code implementation COLING 2020 Wentao Ma, Yiming Cui, Chenglei Si, Ting Liu, Shijin Wang, Guoping Hu

Most pre-trained language models (PLMs) construct word representations at subword level with Byte-Pair Encoding (BPE) or its variations, by which OOV (out-of-vocab) words are almost avoidable.

Language Modelling Question Answering +2

HIT-SCIR at MRP 2020: Transition-based Parser and Iterative Inference Parser

no code implementations CONLL 2020 Longxu Dou, Yunlong Feng, Yuqiu Ji, Wanxiang Che, Ting Liu

This paper describes our submission system (HIT-SCIR) for the CoNLL 2020 shared task: Cross-Framework and Cross-Lingual Meaning Representation Parsing.

Incorporating Commonsense Knowledge into Abstractive Dialogue Summarization via Heterogeneous Graph Networks

1 code implementation CCL 2021 Xiachong Feng, Xiaocheng Feng, Bing Qin, Ting Liu

In detail, we consider utterance and commonsense knowledge as two different types of data and design a Dialogue Heterogeneous Graph Network (D-HGN) for modeling both information.

Abstractive Dialogue Summarization dialogue summary +1

Taking A Closer Look at Synthesis: Fine-grained Attribute Analysis for Person Re-Identification

no code implementations15 Oct 2020 Suncheng Xiang, Yuzhuo Fu, Guanjie You, Ting Liu

Person re-identification (re-ID) plays an important role in applications such as public security and video surveillance.

GPR Person Re-Identification

A Co-Interactive Transformer for Joint Slot Filling and Intent Detection

1 code implementation8 Oct 2020 Libo Qin, Tailu Liu, Wanxiang Che, Bingbing Kang, Sendong Zhao, Ting Liu

Instead of adopting the self-attention mechanism in vanilla Transformer, we propose a co-interactive module to consider the cross-impact by building a bidirectional connection between the two related tasks.

Intent Detection Slot Filling +1

N-LTP: An Open-source Neural Language Technology Platform for Chinese

1 code implementation EMNLP (ACL) 2021 Wanxiang Che, Yunlong Feng, Libo Qin, Ting Liu

We introduce \texttt{N-LTP}, an open-source neural language technology platform supporting six fundamental Chinese NLP tasks: {lexical analysis} (Chinese word segmentation, part-of-speech tagging, and named entity recognition), {syntactic parsing} (dependency parsing), and {semantic parsing} (semantic dependency parsing and semantic role labeling).

Chinese Word Segmentation Dependency Parsing +6

Profile Consistency Identification for Open-domain Dialogue Agents

1 code implementation EMNLP 2020 Haoyu Song, Yan Wang, Wei-Nan Zhang, Zhengyu Zhao, Ting Liu, Xiaojiang Liu

Maintaining a consistent attribute profile is crucial for dialogue agents to naturally converse with humans.

DCR-Net: A Deep Co-Interactive Relation Network for Joint Dialog Act Recognition and Sentiment Classification

no code implementations16 Aug 2020 Libo Qin, Wanxiang Che, Yangming Li, Minheng Ni, Ting Liu

In dialog system, dialog act recognition and sentiment classification are two correlative tasks to capture speakers intentions, where dialog act and sentiment can indicate the explicit and the implicit intentions separately.

Sentiment Analysis

Can We Trust Your Explanations? Sanity Checks for Interpreters in Android Malware Analysis

no code implementations13 Aug 2020 Ming Fan, Wenying Wei, Xiaofei Xie, Yang Liu, Xiaohong Guan, Ting Liu

For this reason, a variety of explanation approaches are proposed to interpret predictions by providing important features.

Cryptography and Security Software Engineering

Conversational Graph Grounded Policy Learning for Open-Domain Conversation Generation

no code implementations ACL 2020 Jun Xu, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, Ting Liu

To address the challenge of policy learning in open-domain multi-turn conversation, we propose to represent prior information about dialog transitions as a graph and learn a graph grounded dialog policy, aimed at fostering a more coherent and controllable dialog.

A Unified Framework for Analyzing and Detecting Malicious Examples of DNN Models

1 code implementation26 Jun 2020 Kaidi Jin, Tianwei Zhang, Chao Shen, Yufei Chen, Ming Fan, Chenhao Lin, Ting Liu

In this paper, we present a unified framework for detecting malicious examples and protecting the inference results of Deep Learning models.

Adversarial Defense

Attribute analysis with synthetic dataset for person re-identification

no code implementations12 Jun 2020 Suncheng Xiang, Yuzhuo Fu, Guanjie You, Ting Liu

To address this problem, firstly, we develop a large-scale synthetic data engine, the salient characteristic of this engine is controllable.

Person Re-Identification

Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension

1 code implementation ACL 2020 Bo Zheng, Haoyang Wen, Yaobo Liang, Nan Duan, Wanxiang Che, Daxin Jiang, Ming Zhou, Ting Liu

Natural Questions is a new challenging machine reading comprehension benchmark with two-grained answers, which are a long answer (typically a paragraph) and a short answer (one or more entities inside the long answer).

Graph Attention Machine Reading Comprehension

Towards Conversational Recommendation over Multi-Type Dialogs

1 code implementation ACL 2020 Zeming Liu, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, Ting Liu

We propose a new task of conversational recommendation over multi-type dialogs, where the bots can proactively and naturally lead a conversation from a non-recommendation dialog (e. g., QA) to a recommendation dialog, taking into account user's interests and feedback.

How Does Selective Mechanism Improve Self-Attention Networks?

1 code implementation ACL 2020 Xinwei Geng, Long-Yue Wang, Xing Wang, Bing Qin, Ting Liu, Zhaopeng Tu

Self-attention networks (SANs) with selective mechanism has produced substantial improvements in various NLP tasks by concentrating on a subset of input words.

Machine Translation Natural Language Inference +1

Multi-Domain Spoken Language Understanding Using Domain- and Task-Aware Parameterization

no code implementations30 Apr 2020 Libo Qin, Minheng Ni, Yue Zhang, Wanxiang Che, Yangming Li, Ting Liu

Spoken language understanding has been addressed as a supervised learning problem, where a set of training data is available for each domain.

Spoken Language Understanding

Benchmarking Robustness of Machine Reading Comprehension Models

1 code implementation Findings (ACL) 2021 Chenglei Si, Ziqing Yang, Yiming Cui, Wentao Ma, Ting Liu, Shijin Wang

To fill this important gap, we construct AdvRACE (Adversarial RACE), a new model-agnostic benchmark for evaluating the robustness of MRC models under four different types of adversarial attacks, including our novel distractor extraction and generation attacks.

Machine Reading Comprehension Natural Language Understanding

Revisiting Pre-Trained Models for Chinese Natural Language Processing

6 code implementations Findings of the Association for Computational Linguistics 2020 Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Shijin Wang, Guoping Hu

Bidirectional Encoder Representations from Transformers (BERT) has shown marvelous improvements across various NLP tasks, and consecutive variants have been proposed to further improve the performance of the pre-trained language models.

Language Modelling

Counterfactual Off-Policy Training for Neural Response Generation

no code implementations29 Apr 2020 Qingfu Zhu, Wei-Nan Zhang, Ting Liu, William Yang Wang

Open-domain dialogue generation suffers from the data insufficiency problem due to the vast size of potential responses.

Dialogue Generation

Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog

1 code implementation ACL 2020 Libo Qin, Xiao Xu, Wanxiang Che, Yue Zhang, Ting Liu

However, there has been relatively little research on how to effectively use data from all domains to improve the performance of each domain and also unseen domains.

Task-Oriented Dialogue Systems

AGIF: An Adaptive Graph-Interactive Framework for Joint Multiple Intent Detection and Slot Filling

1 code implementation Findings of the Association for Computational Linguistics 2020 Libo Qin, Xiao Xu, Wanxiang Che, Ting Liu

Such an interaction layer is applied to each token adaptively, which has the advantage to automatically extract the relevant intents information, making a fine-grained intent information integration for the token-level slot prediction.

Intent Detection Slot Filling +1

A Survey of Document Grounded Dialogue Systems (DGDS)

no code implementations17 Apr 2020 Longxuan Ma, Wei-Nan Zhang, Mingda Li, Ting Liu

We believe that extracting unstructured document(s) information is the future trend of the DS because a great amount of human knowledge lies in these document(s).

General Classification

Is Graph Structure Necessary for Multi-hop Question Answering?

no code implementations EMNLP 2020 Nan Shao, Yiming Cui, Ting Liu, Shijin Wang, Guoping Hu

We construct a strong baseline model to establish that, with the proper use of pre-trained models, graph structure may not be necessary for multi-hop question answering.

Graph Attention Multi-hop Question Answering +1

A Sentence Cloze Dataset for Chinese Machine Reading Comprehension

1 code implementation COLING 2020 Yiming Cui, Ting Liu, Ziqing Yang, Zhipeng Chen, Wentao Ma, Wanxiang Che, Shijin Wang, Guoping Hu

To add diversity in this area, in this paper, we propose a new task called Sentence Cloze-style Machine Reading Comprehension (SC-MRC).

Machine Reading Comprehension

Learning to Select Bi-Aspect Information for Document-Scale Text Content Manipulation

1 code implementation24 Feb 2020 Xiaocheng Feng, Yawei Sun, Bing Qin, Heng Gong, Yibo Sun, Wei Bi, Xiaojiang Liu, Ting Liu

In this paper, we focus on a new practical task, document-scale text content manipulation, which is the opposite of text style transfer and aims to preserve text styles while altering the content.

Style Transfer Text Style Transfer +1

EEV: A Large-Scale Dataset for Studying Evoked Expressions from Video

1 code implementation15 Jan 2020 Jennifer J. Sun, Ting Liu, Alan S. Cowen, Florian Schroff, Hartwig Adam, Gautam Prasad

The ability to predict evoked affect from a video, before viewers watch the video, can help in content creation and video recommendation.

Recommendation Systems Transfer Learning +1

Discriminative Sentence Modeling for Story Ending Prediction

no code implementations19 Dec 2019 Yiming Cui, Wanxiang Che, Wei-Nan Zhang, Ting Liu, Shijin Wang, Guoping Hu

Story Ending Prediction is a task that needs to select an appropriate ending for the given story, which requires the machine to understand the story and sometimes needs commonsense knowledge.

Cloze Test

CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension

no code implementations19 Dec 2019 Xingyi Duan, Baoxin Wang, Ziyue Wang, Wentao Ma, Yiming Cui, Dayong Wu, Shijin Wang, Ting Liu, Tianxiang Huo, Zhen Hu, Heng Wang, Zhiyuan Liu

We present a Chinese judicial reading comprehension (CJRC) dataset which contains approximately 10K documents and almost 50K questions with answers.

Machine Reading Comprehension

GLA in MediaEval 2018 Emotional Impact of Movies Task

no code implementations27 Nov 2019 Jennifer J. Sun, Ting Liu, Gautam Prasad

Towards a better understanding of viewer impact, we present our methods for the MediaEval 2018 Emotional Impact of Movies Task to predict the expected valence and arousal continuously in movies.

Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation

5 code implementations CVPR 2020 Bowen Cheng, Maxwell D. Collins, Yukun Zhu, Ting Liu, Thomas S. Huang, Hartwig Adam, Liang-Chieh Chen

In this work, we introduce Panoptic-DeepLab, a simple, strong, and fast system for panoptic segmentation, aiming to establish a solid baseline for bottom-up methods that can achieve comparable performance of two-stage methods while yielding fast inference speed.

Ranked #3 on Instance Segmentation on Cityscapes test (using extra training data)

Instance Segmentation Panoptic Segmentation

Contextual Recurrent Units for Cloze-style Reading Comprehension

no code implementations14 Nov 2019 Yiming Cui, Wei-Nan Zhang, Wanxiang Che, Ting Liu, Zhipeng Chen, Shijin Wang, Guoping Hu

Recurrent Neural Networks (RNN) are known as powerful models for handling sequential data, and especially widely utilized in various natural language processing tasks.

Reading Comprehension Sentiment Analysis

Improving Machine Reading Comprehension via Adversarial Training

no code implementations9 Nov 2019 Ziqing Yang, Yiming Cui, Wanxiang Che, Ting Liu, Shijin Wang, Guoping Hu

With virtual adversarial training (VAT), we explore the possibility of improving the RC models with semi-supervised learning and prove that examples from a different task are also beneficial.

General Classification Image Classification +2

An Annotation Scheme of A Large-scale Multi-party Dialogues Dataset for Discourse Parsing and Machine Comprehension

no code implementations8 Nov 2019 Jiaqi Li, Ming Liu, Bing Qin, Zihao Zheng, Ting Liu

In this paper, we propose the scheme for annotating large-scale multi-party chat dialogues for discourse parsing and machine comprehension.

Discourse Parsing Machine Reading Comprehension

Transforming Wikipedia into Augmented Data for Query-Focused Summarization

no code implementations8 Nov 2019 Haichao Zhu, Li Dong, Furu Wei, Bing Qin, Ting Liu

The manual construction of a query-focused summarization corpus is costly and timeconsuming.

Data Augmentation

Multi-Input Multi-Output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text

no code implementations IJCNLP 2019 Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh Chawla, Meng Jiang

In this work, we propose a new sequence labeling framework (as well as a new tag schema) to jointly extract the fact and condition tuples from statement sentences.

TAG

IFlyLegal: A Chinese Legal System for Consultation, Law Searching, and Document Analysis

no code implementations IJCNLP 2019 Ziyue Wang, Baoxin Wang, Xingyi Duan, Dayong Wu, Shijin Wang, Guoping Hu, Ting Liu

To our knowledge, IFlyLegal is the first Chinese legal system that employs up-to-date NLP techniques and caters for needs of different user groups, such as lawyers, judges, procurators, and clients.

Natural Language Inference Question Answering +1

Panoptic-DeepLab

2 code implementations10 Oct 2019 Bowen Cheng, Maxwell D. Collins, Yukun Zhu, Ting Liu, Thomas S. Huang, Hartwig Adam, Liang-Chieh Chen

The semantic segmentation branch is the same as the typical design of any semantic segmentation model (e. g., DeepLab), while the instance segmentation branch is class-agnostic, involving a simple instance center regression.

Instance Segmentation Panoptic Segmentation

Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder

no code implementations IJCNLP 2019 Li Du, Xiao Ding, Ting Liu, Zhongyang Li

Understanding event and event-centered commonsense reasoning are crucial for natural language processing (NLP).

Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing

1 code implementation IJCNLP 2019 Yuxuan Wang, Wanxiang Che, Jiang Guo, Yijia Liu, Ting Liu

In this approach, a linear transformation is learned from contextual word alignments to align the contextualized embeddings independently trained in different languages.

Dependency Parsing Language Modelling +2

A Corpus-free State2Seq User Simulator for Task-oriented Dialogue

1 code implementation10 Sep 2019 Yutai Hou, Meng Fang, Wanxiang Che, Ting Liu

The framework builds a user simulator by first generating diverse dialogue data from templates and then build a new State2Seq user simulator on the data.

Event Representation Learning Enhanced with External Commonsense Knowledge

1 code implementation IJCNLP 2019 Xiao Ding, Kuo Liao, Ting Liu, Zhongyang Li, Junwen Duan

Prior work has proposed effective methods to learn event representations that can capture syntactic and semantic information over text corpus, demonstrating their effectiveness for downstream tasks such as script event prediction.

Representation Learning Stock Market Prediction

Table-to-Text Generation with Effective Hierarchical Encoder on Three Dimensions (Row, Column and Time)

1 code implementation IJCNLP 2019 Heng Gong, Xiaocheng Feng, Bing Qin, Ting Liu

To address aforementioned problems, not only do we model each table cell considering other records in the same row, we also enrich table's representation by modeling each table cell in context of other cells in the same column or with historical (time dimension) data respectively.

Table-to-Text Generation Time Series

A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding

2 code implementations IJCNLP 2019 Libo Qin, Wanxiang Che, Yangming Li, Haoyang Wen, Ting Liu

In our framework, we adopt a joint model with Stack-Propagation which can directly use the intent information as input for slot filling, thus to capture the intent semantic knowledge.

Intent Detection Slot Filling +1

ELG: An Event Logic Graph

no code implementations18 Jul 2019 Xiao Ding, Zhongyang Li, Ting Liu, Kuo Liao

The evolution and development of events have their own basic principles, which make events happen sequentially.

Decision Making

Few-Shot Sequence Labeling with Label Dependency Transfer and Pair-wise Embedding

no code implementations20 Jun 2019 Yutai Hou, Zhihan Zhou, Yijia Liu, Ning Wang, Wanxiang Che, Han Liu, Ting Liu

It calculates emission score with similarity based methods and obtains transition score with a specially designed transfer mechanism.

Few-Shot Learning Named Entity Recognition

Pre-Training with Whole Word Masking for Chinese BERT

2 code implementations19 Jun 2019 Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Ziqing Yang

To demonstrate the effectiveness of these models, we create a series of Chinese pre-trained language models as our baselines, including BERT, RoBERTa, ELECTRA, RBT, etc.

Document Classification General Classification +5

Learning to Ask Unanswerable Questions for Machine Reading Comprehension

no code implementations ACL 2019 Haichao Zhu, Li Dong, Furu Wei, Wenhui Wang, Bing Qin, Ting Liu

We also present a way to construct training data for our question generation models by leveraging the existing reading comprehension dataset.

Data Augmentation Machine Reading Comprehension +1

Exploiting Persona Information for Diverse Generation of Conversational Responses

1 code implementation29 May 2019 Haoyu Song, Wei-Nan Zhang, Yiming Cui, Dong Wang, Ting Liu

Giving conversational context with persona information to a chatbot, how to exploit the information to generate diverse and sustainable conversations is still a non-trivial task.

Chatbot

Story Ending Prediction by Transferable BERT

1 code implementation17 May 2019 Zhongyang Li, Xiao Ding, Ting Liu

In this study, we investigate a transferable BERT (TransBERT) training framework, which can transfer not only general language knowledge from large-scale unlabeled data but also specific kinds of knowledge from various semantically related supervised tasks, for a target task.

Language Modelling Natural Language Inference +1

Attribute Acquisition in Ontology based on Representation Learning of Hierarchical Classes and Attributes

no code implementations8 Mar 2019 Tianwen Jiang, Ming Liu, Bing Qin, Ting Liu

This paper investigates an attention-based automatic paradigm called TransATT for attribute acquisition, by learning the representation of hierarchical classes and attributes in Chinese ontology.

Representation Learning

Toward Achieving Robust Low-Level and High-Level Scene Parsing

1 code implementation journal 2019 Bing Shuai, Henghui Ding, Ting Liu, Gang Wang, Xudong Jiang

Furthermore, we introduce a “dense skip” architecture to retain a rich set of low-level information from the pre-trained CNN, which is essential to improve the low-level parsing performance.

Scene Parsing Scene Segmentation

Learning to Refine Source Representations for Neural Machine Translation

no code implementations26 Dec 2018 Xinwei Geng, Long-Yue Wang, Xing Wang, Bing Qin, Ting Liu, Zhaopeng Tu

Neural machine translation (NMT) models generally adopt an encoder-decoder architecture for modeling the entire translation process.

Machine Translation Translation

A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization

1 code implementation14 Dec 2018 Sendong Zhao, Ting Liu, Sicheng Zhao, Fei Wang

State-of-the-art studies have demonstrated the superiority of joint modelling over pipeline implementation for medical named entity recognition and normalization due to the mutual benefits between the two processes.

Medical Named Entity Recognition Multi-Task Learning

An AMR Aligner Tuned by Transition-based Parser

1 code implementation EMNLP 2018 Yijia Liu, Wanxiang Che, Bo Zheng, Bing Qin, Ting Liu

In this paper, we propose a new rich resource enhanced AMR aligner which produces multiple alignments and a new transition system for AMR parsing along with its oracle parser.

AMR Parsing POS

Adaptive Multi-pass Decoder for Neural Machine Translation

no code implementations EMNLP 2018 Xinwei Geng, Xiaocheng Feng, Bing Qin, Ting Liu

Although end-to-end neural machine translation (NMT) has achieved remarkable progress in the recent years, the idea of adopting multi-pass decoding mechanism into conventional NMT is not well explored.

Machine Translation Translation

Retrieval-Enhanced Adversarial Training for Neural Response Generation

no code implementations ACL 2019 Qingfu Zhu, Lei Cui, Wei-Nan Zhang, Furu Wei, Ting Liu

Dialogue systems are usually built on either generation-based or retrieval-based approaches, yet they do not benefit from the advantages of different models.

A Detection and Segmentation Architecture for Skin Lesion Segmentation on Dermoscopy Images

no code implementations11 Sep 2018 Chengyao Qian, Ting Liu, Hao Jiang, Zhe Wang, Pengfei Wang, Mingxin Guan, Biao Sun

This report summarises our method and validation results for the ISIC Challenge 2018 - Skin Lesion Analysis Towards Melanoma Detection - Task 1: Lesion Segmentation.

Lesion Segmentation

Zero Pronoun Resolution with Attention-based Neural Network

1 code implementation COLING 2018 Qingyu Yin, Yu Zhang, Wei-Nan Zhang, Ting Liu, William Yang Wang

Recent neural network methods for zero pronoun resolution explore multiple models for generating representation vectors for zero pronouns and their candidate antecedents.

Chinese Zero Pronoun Resolution

Generating Reasonable and Diversified Story Ending Using Sequence to Sequence Model with Adversarial Training

no code implementations COLING 2018 Zhongyang Li, Xiao Ding, Ting Liu

In this paper, we propose using adversarial training augmented Seq2Seq model to generate reasonable and diversified story endings given a story context.

Cloze Test Information Retrieval +1

Context-Sensitive Generation of Open-Domain Conversational Responses

no code implementations COLING 2018 Wei-Nan Zhang, Yiming Cui, Yifa Wang, Qingfu Zhu, Lingzhi Li, Lianqiang Zhou, Ting Liu

Despite the success of existing works on single-turn conversation generation, taking the coherence in consideration, human conversing is actually a context-sensitive process.

Information Retrieval Machine Translation

Learning Target-Specific Representations of Financial News Documents For Cumulative Abnormal Return Prediction

1 code implementation COLING 2018 Junwen Duan, Yue Zhang, Xiao Ding, Ching-Yun Chang, Ting Liu

The model uses a target-sensitive representation of the news abstract to weigh sentences in the news content, so as to select and combine the most informative sentences for market modeling.

Information Retrieval Stock Market Prediction

Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding

1 code implementation COLING 2018 Yutai Hou, Yijia Liu, Wanxiang Che, Ting Liu

In this paper, we study the problem of data augmentation for language understanding in task-oriented dialogue system.

Text Augmentation