Search Results for author: Duyu Tang

Found 69 papers, 23 papers with code

Analytical Reasoning of Text

1 code implementation Findings (NAACL) 2022 Wanjun Zhong, Siyuan Wang, Duyu Tang, Zenan Xu, Daya Guo, Yining Chen, Jiahai Wang, Jian Yin, Ming Zhou, Nan Duan

In this paper, we study the challenge of analytical reasoning of text and collect a new dataset consisting of questions from the Law School Admission Test from 1991 to 2016.

Android in the Zoo: Chain-of-Action-Thought for GUI Agents

1 code implementation5 Mar 2024 Jiwen Zhang, Jihao Wu, Yihua Teng, Minghui Liao, Nuo Xu, Xiao Xiao, Zhongyu Wei, Duyu Tang

To address this, this work presents Chain-of-Action-Thought (dubbed CoAT), which takes the description of the previous actions, the current screen, and more importantly the action thinking of what actions should be performed and the outcomes led by the chosen action.

Language Modelling Large Language Model

Emage: Non-Autoregressive Text-to-Image Generation

no code implementations22 Dec 2023 Zhangyin Feng, Runyi Hu, Liangxin Liu, Fan Zhang, Duyu Tang, Yong Dai, Xiaocheng Feng, Jiwei Li, Bing Qin, Shuming Shi

Compared with autoregressive baselines that needs to run one thousand times, our model only runs 16 times to generate images of competitive quality with an order of magnitude lower inference latency.

Denoising Text-to-Image Generation

SkillNet-X: A Multilingual Multitask Model with Sparsely Activated Skills

no code implementations28 Jun 2023 Zhangyin Feng, Yong Dai, Fan Zhang, Duyu Tang, Xiaocheng Feng, Shuangzhi Wu, Bing Qin, Yunbo Cao, Shuming Shi

Traditional multitask learning methods basically can only exploit common knowledge in task- or language-wise, which lose either cross-language or cross-task knowledge.

Natural Language Understanding

Improved Visual Story Generation with Adaptive Context Modeling

no code implementations26 May 2023 Zhangyin Feng, Yuchen Ren, Xinmiao Yu, Xiaocheng Feng, Duyu Tang, Shuming Shi, Bing Qin

Diffusion models developed on top of powerful text-to-image generation models like Stable Diffusion achieve remarkable success in visual story generation.

Story Generation Story Visualization +1

STOA-VLP: Spatial-Temporal Modeling of Object and Action for Video-Language Pre-training

no code implementations20 Feb 2023 Weihong Zhong, Mao Zheng, Duyu Tang, Xuan Luo, Heng Gong, Xiaocheng Feng, Bing Qin

Although large-scale video-language pre-training models, which usually build a global alignment between the video and the text, have achieved remarkable progress on various downstream tasks, the idea of adopting fine-grained information during the pre-training stage is not well explored.

Language Modelling Object +5

Effidit: Your AI Writing Assistant

no code implementations3 Aug 2022 Shuming Shi, Enbo Zhao, Duyu Tang, Yan Wang, Piji Li, Wei Bi, Haiyun Jiang, Guoping Huang, Leyang Cui, Xinting Huang, Cong Zhou, Yong Dai, Dongyang Ma

In Effidit, we significantly expand the capacities of a writing assistant by providing functions in five categories: text completion, error checking, text polishing, keywords to sentences (K2S), and cloud input methods (cloud IME).

Keywords to Sentences Retrieval +3

One Model, Multiple Modalities: A Sparsely Activated Approach for Text, Sound, Image, Video and Code

no code implementations12 May 2022 Yong Dai, Duyu Tang, Liangxin Liu, Minghuan Tan, Cong Zhou, Jingquan Wang, Zhangyin Feng, Fan Zhang, Xueyu Hu, Shuming Shi

Moreover, our model supports self-supervised pretraining with the same sparsely activated way, resulting in better initialized parameters for different modalities.

Image Retrieval Retrieval

Pretraining Chinese BERT for Detecting Word Insertion and Deletion Errors

no code implementations26 Apr 2022 Cong Zhou, Yong Dai, Duyu Tang, Enbo Zhao, Zhangyin Feng, Li Kuang, Shuming Shi

We achieve this by introducing a special token \texttt{[null]}, the prediction of which stands for the non-existence of a word.

Language Modelling Masked Language Modeling +1

SkillNet-NLG: General-Purpose Natural Language Generation with a Sparsely Activated Approach

no code implementations26 Apr 2022 Junwei Liao, Duyu Tang, Fan Zhang, Shuming Shi

We present SkillNet-NLG, a sparsely activated approach that handles many natural language generation tasks with one model.

Multi-Task Learning Text Generation

AR-LSAT: Investigating Analytical Reasoning of Text

1 code implementation14 Apr 2021 Wanjun Zhong, Siyuan Wang, Duyu Tang, Zenan Xu, Daya Guo, Jiahai Wang, Jian Yin, Ming Zhou, Nan Duan

Analytical reasoning is an essential and challenging task that requires a system to analyze a scenario involving a set of particular circumstances and perform reasoning over it to make conclusions.

Syntax-Enhanced Pre-trained Model

1 code implementation ACL 2021 Zenan Xu, Daya Guo, Duyu Tang, Qinliang Su, Linjun Shou, Ming Gong, Wanjun Zhong, Xiaojun Quan, Nan Duan, Daxin Jiang

We study the problem of leveraging the syntactic structure of text to enhance pre-trained models such as BERT and RoBERTa.

Entity Typing Question Answering +1

Machine Reasoning: Technology, Dilemma and Future

no code implementations EMNLP 2020 Nan Duan, Duyu Tang, Ming Zhou

Machine reasoning research aims to build interpretable AI systems that can solve problems or draw conclusions from what they are told (i. e. facts and observations) and already know (i. e. models, common sense and knowledge) under certain constraints.

Common Sense Reasoning

Neural Deepfake Detection with Factual Structure of Text

1 code implementation EMNLP 2020 Wanjun Zhong, Duyu Tang, Zenan Xu, Ruize Wang, Nan Duan, Ming Zhou, Jiahai Wang, Jian Yin

To address this, we propose a graph-based model that utilizes the factual structure of a document for deepfake detection of text.

DeepFake Detection Face Swapping +1

CodeBLEU: a Method for Automatic Evaluation of Code Synthesis

2 code implementations22 Sep 2020 Shuo Ren, Daya Guo, Shuai Lu, Long Zhou, Shujie Liu, Duyu Tang, Neel Sundaresan, Ming Zhou, Ambrosio Blanco, Shuai Ma

Evaluation metrics play a vital role in the growth of an area as it defines the standard of distinguishing between good and bad models.

Code Translation Translation

GraphCodeBERT: Pre-training Code Representations with Data Flow

1 code implementation ICLR 2021 Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie Liu, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, Michele Tufano, Shao Kun Deng, Colin Clement, Dawn Drain, Neel Sundaresan, Jian Yin, Daxin Jiang, Ming Zhou

Instead of taking syntactic-level structure of code like abstract syntax tree (AST), we use data flow in the pre-training stage, which is a semantic-level structure of code that encodes the relation of "where-the-value-comes-from" between variables.

Clone Detection Code Completion +7

Evidence-Aware Inferential Text Generation with Vector Quantised Variational AutoEncoder

1 code implementation ACL 2020 Daya Guo, Duyu Tang, Nan Duan, Jian Yin, Daxin Jiang, Ming Zhou

Generating inferential texts about an event in different perspectives requires reasoning over different contexts that the event occurs.

Common Sense Reasoning Text Generation

Pre-training Text Representations as Meta Learning

no code implementations12 Apr 2020 Shangwen Lv, Yuechen Wang, Daya Guo, Duyu Tang, Nan Duan, Fuqing Zhu, Ming Gong, Linjun Shou, Ryan Ma, Daxin Jiang, Guihong Cao, Ming Zhou, Songlin Hu

In this work, we introduce a learning algorithm which directly optimizes model's ability to learn text representations for effective learning of downstream tasks.

Language Modelling Meta-Learning +2

Neural Semantic Parsing in Low-Resource Settings with Back-Translation and Meta-Learning

no code implementations12 Sep 2019 Yibo Sun, Duyu Tang, Nan Duan, Yeyun Gong, Xiaocheng Feng, Bing Qin, Daxin Jiang

Neural semantic parsing has achieved impressive results in recent years, yet its success relies on the availability of large amounts of supervised data.

Meta-Learning Semantic Parsing +1

Reasoning Over Semantic-Level Graph for Fact Checking

no code implementations ACL 2020 Wanjun Zhong, Jingjing Xu, Duyu Tang, Zenan Xu, Nan Duan, Ming Zhou, Jiahai Wang, Jian Yin

We evaluate our system on FEVER, a benchmark dataset for fact checking, and find that rich structural information is helpful and both our graph-based mechanisms improve the accuracy.

Claim Verification Fact Checking +4

Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing

no code implementations ACL 2019 Daya Guo, Duyu Tang, Nan Duan, Ming Zhou, Jian Yin

In this paper, we present an approach to incorporate retrieved datapoints as supporting evidence for context-dependent semantic parsing, such as generating source code conditioned on the class environment.

Meta-Learning Retrieval +1

Deep Reason: A Strong Baseline for Real-World Visual Reasoning

no code implementations24 May 2019 Chenfei Wu, Yanzhao Zhou, Gen Li, Nan Duan, Duyu Tang, Xiaojie Wang

This paper presents a strong baseline for real-world visual reasoning (GQA), which achieves 60. 93% in GQA 2019 challenge and won the sixth place.

Visual Reasoning

Knowledge Based Machine Reading Comprehension

no code implementations12 Sep 2018 Yibo Sun, Daya Guo, Duyu Tang, Nan Duan, Zhao Yan, Xiaocheng Feng, Bing Qin

Machine reading comprehension (MRC) requires reasoning about both the knowledge involved in a document and knowledge about the world.

Machine Reading Comprehension Question Answering +2

Improving Question Answering by Commonsense-Based Pre-Training

no code implementations5 Sep 2018 Wanjun Zhong, Duyu Tang, Nan Duan, Ming Zhou, Jiahai Wang, Jian Yin

Although neural network approaches achieve remarkable success on a variety of NLP tasks, many of them struggle to answer questions that require commonsense knowledge.

Question Answering

Learning to Collaborate for Question Answering and Asking

no code implementations NAACL 2018 Duyu Tang, Nan Duan, Zhao Yan, Zhirui Zhang, Yibo Sun, Shujie Liu, Yuanhua Lv, Ming Zhou

Secondly, directly applying GAN that regards all the generated questions as negative instances could not improve the accuracy of the QA model.

Answer Selection Generative Adversarial Network +2

Table-to-Text: Describing Table Region with Natural Language

no code implementations29 May 2018 Junwei Bao, Duyu Tang, Nan Duan, Zhao Yan, Yuanhua Lv, Ming Zhou, Tiejun Zhao

The model maps a row from a table to a continuous vector and then generates a natural language sentence by leveraging the semantics of a table.

Language Modelling Sentence

Assertion-based QA with Question-Aware Open Information Extraction

no code implementations23 Jan 2018 Zhao Yan, Duyu Tang, Nan Duan, Shujie Liu, Wendi Wang, Daxin Jiang, Ming Zhou, Zhoujun Li

We present assertion based question answering (ABQA), an open domain question answering task that takes a question and a passage as inputs, and outputs a semi-structured assertion consisting of a subject, a predicate and a list of arguments.

Learning-To-Rank Open-Domain Question Answering +2

Question Generation for Question Answering

no code implementations EMNLP 2017 Nan Duan, Duyu Tang, Peng Chen, Ming Zhou

This paper presents how to generate questions from given passages using neural networks, where large scale QA pairs are automatically crawled and processed from Community-QA website, and used as training data.

Chatbot Question Answering +5

Content-Based Table Retrieval for Web Queries

no code implementations8 Jun 2017 Zhao Yan, Duyu Tang, Nan Duan, Junwei Bao, Yuanhua Lv, Ming Zhou, Zhoujun Li

Understanding the connections between unstructured text and semi-structured table is an important yet neglected problem in natural language processing.

Table Retrieval

Question Answering and Question Generation as Dual Tasks

no code implementations7 Jun 2017 Duyu Tang, Nan Duan, Tao Qin, Zhao Yan, Ming Zhou

On one side, the QA model judges whether the generated question of a QG model is relevant to the answer.

Question Answering Question Generation +1

Aspect Level Sentiment Classification with Deep Memory Network

8 code implementations EMNLP 2016 Duyu Tang, Bing Qin, Ting Liu

Such importance degree and text representation are calculated with multiple computational layers, each of which is a neural attention model over an external memory.

Aspect-Based Sentiment Analysis (ABSA) General Classification +1

A Planning based Framework for Essay Generation

no code implementations18 Dec 2015 Bing Qin, Duyu Tang, Xinwei Geng, Dandan Ning, Jiahao Liu, Ting Liu

Generating an article automatically with computer program is a challenging task in artificial intelligence and natural language processing.

Sentence

Radical-Enhanced Chinese Character Embedding

no code implementations18 Apr 2014 Yaming Sun, Lei Lin, Duyu Tang, Nan Yang, Zhenzhou Ji, Xiaolong Wang

We present a method to leverage radical for learning Chinese character embedding.

Chinese Word Segmentation

Emotion Analysis Platform on Chinese Microblog

no code implementations28 Mar 2014 Duyu Tang, Bing Qin, Ting Liu, Qiuhui Shi

In order to analyze the emotional changes in accordance with time and space, this paper presents an Emotion Analysis Platform (EAP), which explores the emotional distribution of each province, so that can monitor the global pulse of each province in China.

Emotion Recognition

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