Search Results for author: Dongmei Zhang

Found 73 papers, 33 papers with code

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

``What Do You Mean by That?'' A Parser-Independent Interactive Approach for Enhancing Text-to-SQL

no code implementations EMNLP 2020 Yuntao Li, Bei Chen, Qian Liu, Yan Gao, Jian-Guang Lou, Yan Zhang, Dongmei Zhang

In Natural Language Interfaces to Databases systems, the text-to-SQL technique allows users to query databases by using natural language questions.


On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering

1 code implementation6 Jun 2023 Jiayan Guo, Lun Du, Xu Chen, Xiaojun Ma, Qiang Fu, Shi Han, Dongmei Zhang, Yan Zhang

Graph CF has attracted more and more attention in recent years due to its effectiveness in leveraging high-order information in the user-item bipartite graph for better recommendations.

Collaborative Filtering Recommendation Systems

Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines

no code implementations4 Jun 2023 Dezhan Tu, Yeye He, Weiwei Cui, Song Ge, Haidong Zhang, Han Shi, Dongmei Zhang, Surajit Chaudhuri

Data pipelines are widely employed in modern enterprises to power a variety of Machine-Learning (ML) and Business-Intelligence (BI) applications.

Leveraging LLMs for KPIs Retrieval from Hybrid Long-Document: A Comprehensive Framework and Dataset

no code implementations24 May 2023 Chongjian Yue, Xinrun Xu, Xiaojun Ma, Lun Du, Hengyu Liu, Zhiming Ding, Yanbing Jiang, Shi Han, Dongmei Zhang

We propose an Automated Financial Information Extraction (AFIE) framework that enhances LLMs' ability to comprehend and extract information from financial reports.


Introspective Tips: Large Language Model for In-Context Decision Making

no code implementations19 May 2023 Liting Chen, Lu Wang, Hang Dong, Yali Du, Jie Yan, Fangkai Yang, Shuang Li, Pu Zhao, Si Qin, Saravan Rajmohan, QIngwei Lin, Dongmei Zhang

The emergence of large language models (LLMs) has substantially influenced natural language processing, demonstrating exceptional results across various tasks.

Decision Making Language Modelling +1

Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering

1 code implementation19 May 2023 Zezhong Wang, Fangkai Yang, Pu Zhao, Lu Wang, Jue Zhang, Mohit Garg, QIngwei Lin, Dongmei Zhang

Large Language Model (LLM) has gained popularity and achieved remarkable results in open-domain tasks, but its performance in real industrial domain-specific scenarios is average since there is no specific knowledge in it.

Language Modelling Question Answering +1

How Do In-Context Examples Affect Compositional Generalization?

no code implementations8 May 2023 Shengnan An, Zeqi Lin, Qiang Fu, Bei Chen, Nanning Zheng, Jian-Guang Lou, Dongmei Zhang

Compositional generalization--understanding unseen combinations of seen primitives--is an essential reasoning capability in human intelligence.

Towards Efficient Fine-tuning of Pre-trained Code Models: An Experimental Study and Beyond

1 code implementation11 Apr 2023 Ensheng Shi, Yanlin Wang, Hongyu Zhang, Lun Du, Shi Han, Dongmei Zhang, Hongbin Sun

Our experimental study shows that (1) lexical, syntactic and structural properties of source code are encoded in the lower, intermediate, and higher layers, respectively, while the semantic property spans across the entire model.

Demonstration of InsightPilot: An LLM-Empowered Automated Data Exploration System

no code implementations2 Apr 2023 Pingchuan Ma, Rui Ding, Shuai Wang, Shi Han, Dongmei Zhang

In brief, an IQuery is an abstraction and automation of data analysis operations, which mimics the approach of data analysts and simplifies the exploration process for users.

Language Modelling

LayoutDiffusion: Improving Graphic Layout Generation by Discrete Diffusion Probabilistic Models

no code implementations21 Mar 2023 Junyi Zhang, Jiaqi Guo, Shizhao Sun, Jian-Guang Lou, Dongmei Zhang

To tackle the challenge, we summarize three critical factors for achieving a mild forward process for the layout, i. e., legality, coordinate proximity and type disruption.

Layout Design

Robust Mid-Pass Filtering Graph Convolutional Networks

1 code implementation16 Feb 2023 Jincheng Huang, Lun Du, Xu Chen, Qiang Fu, Shi Han, Dongmei Zhang

Theoretical analyses guarantee the robustness of signals through the mid-pass filter, and we also shed light on the properties of different frequency signals under adversarial attacks.

Adversarial Attack Node Classification

Conservative State Value Estimation for Offline Reinforcement Learning

1 code implementation14 Feb 2023 Liting Chen, Jie Yan, Zhengdao Shao, Lu Wang, QIngwei Lin, Dongmei Zhang

In this paper, we propose Conservative State Value Estimation (CSVE), a new approach that learns conservative V-function via directly imposing penalty on OOD states.

D4RL reinforcement-learning +1

Homophily-oriented Heterogeneous Graph Rewiring

no code implementations13 Feb 2023 Jiayan Guo, Lun Du, Wendong Bi, Qiang Fu, Xiaojun Ma, Xu Chen, Shi Han, Dongmei Zhang, Yan Zhang

To this end, we propose HDHGR, a homophily-oriented deep heterogeneous graph rewiring approach that modifies the HG structure to increase the performance of HGNN.

LUNA: Language Understanding with Number Augmentations on Transformers via Number Plugins and Pre-training

1 code implementation6 Dec 2022 Hongwei Han, Jialiang Xu, Mengyu Zhou, Yijia Shao, Shi Han, Dongmei Zhang

But current approaches to rich-number tasks with transformer-based language models abandon or lose some of the numeracy information - e. g., breaking numbers into sub-word tokens - which leads to many number-related errors.

Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning

no code implementations21 Nov 2022 Junjie Sheng, Lu Wang, Fangkai Yang, Bo Qiao, Hang Dong, Xiangfeng Wang, Bo Jin, Jun Wang, Si Qin, Saravan Rajmohan, QIngwei Lin, Dongmei Zhang

To address these two limitations, this paper formulates the oversubscription for cloud as a chance-constrained optimization problem and propose an effective Chance Constrained Multi-Agent Reinforcement Learning (C2MARL) method to solve this problem.

Multi-agent Reinforcement Learning reinforcement-learning +1

FormLM: Recommending Creation Ideas for Online Forms by Modelling Semantic and Structural Information

no code implementations10 Nov 2022 Yijia Shao, Mengyu Zhou, Yifan Zhong, Tao Wu, Hongwei Han, Shi Han, Gideon Huang, Dongmei Zhang

To assist form designers, in this work we present FormLM to model online forms (by enhancing pre-trained language model with form structural information) and recommend form creation ideas (including question / options recommendations and block type suggestion).

Language Modelling

Unveiling the Black Box of PLMs with Semantic Anchors: Towards Interpretable Neural Semantic Parsing

no code implementations4 Oct 2022 Lunyiu Nie, Jiuding Sun, Yanlin Wang, Lun Du, Lei Hou, Juanzi Li, Shi Han, Dongmei Zhang, Jidong Zhai

The recent prevalence of pretrained language models (PLMs) has dramatically shifted the paradigm of semantic parsing, where the mapping from natural language utterances to structured logical forms is now formulated as a Seq2Seq task.

Semantic Parsing

Learning Rate Perturbation: A Generic Plugin of Learning Rate Schedule towards Flatter Local Minima

no code implementations25 Aug 2022 Hengyu Liu, Qiang Fu, Lun Du, Tiancheng Zhang, Ge Yu, Shi Han, Dongmei Zhang

Learning rate is one of the most important hyper-parameters that has a significant influence on neural network training.

LayoutFormer++: Conditional Graphic Layout Generation via Constraint Serialization and Decoding Space Restriction

no code implementations CVPR 2023 Zhaoyun Jiang, Jiaqi Guo, Shizhao Sun, Huayu Deng, Zhongkai Wu, Vuksan Mijovic, Zijiang James Yang, Jian-Guang Lou, Dongmei Zhang

First, to flexibly handle diverse constraints, we propose a constraint serialization scheme, which represents different user constraints as sequences of tokens with a predefined format.

MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution

1 code implementation15 Aug 2022 Wendong Bi, Lun Du, Qiang Fu, Yanlin Wang, Shi Han, Dongmei Zhang

Graph Neural Networks (GNNs) have shown expressive performance on graph representation learning by aggregating information from neighbors.

Graph Representation Learning

ASTA: Learning Analytical Semantics over Tables for Intelligent Data Analysis and Visualization

no code implementations1 Aug 2022 Lingbo Li, Tianle Li, Xinyi He, Mengyu Zhou, Shi Han, Dongmei Zhang

ASTA framework extracts data features by designing signatures based on expert knowledge, and enables data referencing at field- (chart) or cell-level (conditional formatting) with pre-trained models.

XInsight: eXplainable Data Analysis Through The Lens of Causality

no code implementations26 Jul 2022 Pingchuan Ma, Rui Ding, Shuai Wang, Shi Han, Dongmei Zhang

XInsight is a three-module, end-to-end pipeline designed to extract causal graphs, translate causal primitives into XDA semantics, and quantify the quantitative contribution of each explanation to a data fact.

Decision Making

PLOG: Table-to-Logic Pretraining for Logical Table-to-Text Generation

1 code implementation25 May 2022 Ao Liu, Haoyu Dong, Naoaki Okazaki, Shi Han, Dongmei Zhang

However, directly learning the logical inference knowledge from table-text pairs is very difficult for neural models because of the ambiguity of natural language and the scarcity of parallel data.

Table-to-Text Generation

TaCube: Pre-computing Data Cubes for Answering Numerical-Reasoning Questions over Tabular Data

1 code implementation25 May 2022 Fan Zhou, Mengkang Hu, Haoyu Dong, Zhoujun Cheng, Shi Han, Dongmei Zhang

Existing auto-regressive pre-trained language models (PLMs) like T5 and BART, have been well applied to table question answering by UNIFIEDSKG and TAPEX, respectively, and demonstrated state-of-the-art results on multiple benchmarks.

Question Answering

OneLabeler: A Flexible System for Building Data Labeling Tools

1 code implementation27 Mar 2022 Yu Zhang, Yun Wang, Haidong Zhang, Bin Zhu, Siming Chen, Dongmei Zhang

In this paper, we propose a conceptual framework for data labeling and OneLabeler based on the conceptual framework to support easy building of labeling tools for diverse usage scenarios.

Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks

no code implementations24 Jan 2022 Haoyu Dong, Zhoujun Cheng, Xinyi He, Mengyu Zhou, Anda Zhou, Fan Zhou, Ao Liu, Shi Han, Dongmei Zhang

Since a vast number of tables can be easily collected from web pages, spreadsheets, PDFs, and various other document types, a flurry of table pre-training frameworks have been proposed following the success of text and images, and they have achieved new state-of-the-arts on various tasks such as table question answering, table type recognition, column relation classification, table search, formula prediction, etc.

Denoising Question Answering +2

Source Free Unsupervised Graph Domain Adaptation

no code implementations2 Dec 2021 Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang

They utilize labels from the source domain as the supervision signal and are jointly trained on both the source graph and the target graph.

Domain Adaptation Node Classification

A Surrogate Objective Framework for Prediction+Programming with Soft Constraints

no code implementations NeurIPS 2021 Kai Yan, Jie Yan, Chuan Luo, Liting Chen, QIngwei Lin, Dongmei Zhang

Prediction+optimization is a common real-world paradigm where we have to predict problem parameters before solving the optimization problem.

Portfolio Optimization

Neuron with Steady Response Leads to Better Generalization

no code implementations30 Nov 2021 Qiang Fu, Lun Du, Haitao Mao, Xu Chen, Wei Fang, Shi Han, Dongmei Zhang

Based on the analysis results, we articulate the Neuron Steadiness Hypothesis: the neuron with similar responses to instances of the same class leads to better generalization.

Inductive Bias

A Surrogate Objective Framework for Prediction+Optimization with Soft Constraints

1 code implementation22 Nov 2021 Kai Yan, Jie Yan, Chuan Luo, Liting Chen, QIngwei Lin, Dongmei Zhang

Prediction+optimization is a common real-world paradigm where we have to predict problem parameters before solving the optimization problem.

Portfolio Optimization

A Unified and Fast Interpretable Model for Predictive Analytics

no code implementations16 Nov 2021 Yuanyuan Jiang, Rui Ding, Tianchi Qiao, Yunan Zhu, Shi Han, Dongmei Zhang

Predictive analytics is human involved, thus the machine learning model is preferred to be interpretable.

Decision Making

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily

1 code implementation29 Oct 2021 Lun Du, Xiaozhou Shi, Qiang Fu, Xiaojun Ma, Hengyu Liu, Shi Han, Dongmei Zhang

For node-level tasks, GNNs have strong power to model the homophily property of graphs (i. e., connected nodes are more similar) while their ability to capture the heterophily property is often doubtful.

Graph Attention

ML4C: Seeing Causality Through Latent Vicinity

1 code implementation NeurIPS 2021 Haoyue Dai, Rui Ding, Yuanyuan Jiang, Shi Han, Dongmei Zhang

Starting from seeing that SCL is not better than random guessing if the learning target is non-identifiable a priori, we propose a two-phase paradigm for SCL by explicitly considering structure identifiability.

FORTAP: Using Formulas for Numerical-Reasoning-Aware Table Pretraining

1 code implementation ACL 2022 Zhoujun Cheng, Haoyu Dong, Ran Jia, Pengfei Wu, Shi Han, Fan Cheng, Dongmei Zhang

In this paper, we find that the spreadsheet formula, which performs calculations on numerical values in tables, is naturally a strong supervision of numerical reasoning.

HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation

1 code implementation ACL 2022 Zhoujun Cheng, Haoyu Dong, Zhiruo Wang, Ran Jia, Jiaqi Guo, Yan Gao, Shi Han, Jian-Guang Lou, Dongmei Zhang

HiTab provides 10, 686 QA pairs and descriptive sentences with well-annotated quantity and entity alignment on 3, 597 tables with broad coverage of table hierarchies and numerical reasoning types.

Entity Alignment Question Answering +1

Neuron Campaign for Initialization Guided by Information Bottleneck Theory

1 code implementation14 Aug 2021 Haitao Mao, Xu Chen, Qiang Fu, Lun Du, Shi Han, Dongmei Zhang

Initialization plays a critical role in the training of deep neural networks (DNN).

On the Evaluation of Neural Code Summarization

1 code implementation15 Jul 2021 Ensheng Shi, Yanlin Wang, Lun Du, Junjie Chen, Shi Han, Hongyu Zhang, Dongmei Zhang, Hongbin Sun

To achieve a profound understanding of how far we are from solving this problem and provide suggestions to future research, in this paper, we conduct a systematic and in-depth analysis of 5 state-of-the-art neural code summarization models on 6 widely used BLEU variants, 4 pre-processing operations and their combinations, and 3 widely used datasets.

Code Summarization Source Code Summarization

On the Evaluation of Commit Message Generation Models: An Experimental Study

1 code implementation12 Jul 2021 Wei Tao, Yanlin Wang, Ensheng Shi, Lun Du, Shi Han, Hongyu Zhang, Dongmei Zhang, Wenqiang Zhang

We find that: (1) Different variants of the BLEU metric are used in previous works, which affects the evaluation and understanding of existing methods.


Is a Single Model Enough? MuCoS: A Multi-Model Ensemble Learning for Semantic Code Search

1 code implementation10 Jul 2021 Lun Du, Xiaozhou Shi, Yanlin Wang, Ensheng Shi, Shi Han, Dongmei Zhang

On the other hand, as a specific query may focus on one or several perspectives, it is difficult for a single query representation module to represent different user intents.

Code Search Data Augmentation +1

TableSense: Spreadsheet Table Detection with Convolutional Neural Networks

1 code implementation25 Jun 2021 Haoyu Dong, Shijie Liu, Shi Han, Zhouyu Fu, Dongmei Zhang

Spreadsheet table detection is the task of detecting all tables on a given sheet and locating their respective ranges.

Active Learning Boundary Detection +1

TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data

no code implementations6 Jun 2021 Lun Du, Fei Gao, Xu Chen, Ran Jia, Junshan Wang, Jiang Zhang, Shi Han, Dongmei Zhang

To simultaneously extract spatial and relational information from tables, we propose a novel neural network architecture, TabularNet.

graph construction

Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective

no code implementations17 May 2021 Lun Du, Xu Chen, Fei Gao, Kunqing Xie, Shi Han, Dongmei Zhang

Network Embedding aims to learn a function mapping the nodes to Euclidean space contribute to multiple learning analysis tasks on networks.

Link Prediction Network Embedding +1

Iterative Utterance Segmentation for Neural Semantic Parsing

no code implementations13 Dec 2020 Yinuo Guo, Zeqi Lin, Jian-Guang Lou, Dongmei Zhang

Experiments on Geo, ComplexWebQuestions, and Formulas show that our framework can consistently improve performances of neural semantic parsers in different domains.

Semantic Parsing

Revisiting Iterative Back-Translation from the Perspective of Compositional Generalization

no code implementations8 Dec 2020 Yinuo Guo, Hualei Zhu, Zeqi Lin, Bei Chen, Jian-Guang Lou, Dongmei Zhang

Human intelligence exhibits compositional generalization (i. e., the capacity to understand and produce unseen combinations of seen components), but current neural seq2seq models lack such ability.


"What Do You Mean by That?" A Parser-Independent Interactive Approach for Enhancing Text-to-SQL

1 code implementation9 Nov 2020 Yuntao Li, Bei Chen, Qian Liu, Yan Gao, Jian-Guang Lou, Yan Zhang, Dongmei Zhang

In Natural Language Interfaces to Databases systems, the text-to-SQL technique allows users to query databases by using natural language questions.


TUTA: Tree-based Transformers for Generally Structured Table Pre-training

1 code implementation21 Oct 2020 Zhiruo Wang, Haoyu Dong, Ran Jia, Jia Li, Zhiyi Fu, Shi Han, Dongmei Zhang

First, we devise a unified tree-based structure, called a bi-dimensional coordinate tree, to describe both the spatial and hierarchical information of generally structured tables.

Compositional Generalization by Learning Analytical Expressions

1 code implementation NeurIPS 2020 Qian Liu, Shengnan An, Jian-Guang Lou, Bei Chen, Zeqi Lin, Yan Gao, Bin Zhou, Nanning Zheng, Dongmei Zhang

Compositional generalization is a basic and essential intellective capability of human beings, which allows us to recombine known parts readily.

Hierarchical Reinforcement Learning

You Impress Me: Dialogue Generation via Mutual Persona Perception

1 code implementation ACL 2020 Qian Liu, Yihong Chen, Bei Chen, Jian-Guang Lou, Zixuan Chen, Bin Zhou, Dongmei Zhang

Despite the continuing efforts to improve the engagingness and consistency of chit-chat dialogue systems, the majority of current work simply focus on mimicking human-like responses, leaving understudied the aspects of modeling understanding between interlocutors.

Dialogue Generation

How Far are We from Effective Context Modeling? An Exploratory Study on Semantic Parsing in Context

1 code implementation3 Feb 2020 Qian Liu, Bei Chen, Jiaqi Guo, Jian-Guang Lou, Bin Zhou, Dongmei Zhang

Recently semantic parsing in context has received considerable attention, which is challenging since there are complex contextual phenomena.

Semantic Parsing

Data-Anonymous Encoding for Text-to-SQL Generation

no code implementations IJCNLP 2019 Zhen Dong, Shizhao Sun, Hongzhi Liu, Jian-Guang Lou, Dongmei Zhang

On text-to-SQL generation, the input utterance usually contains lots of tokens that are related to column names or cells in the table, called \textit{table-related tokens}.


A Hybrid Semantic Parsing Approach for Tabular Data Analysis

no code implementations23 Oct 2019 Yan Gao, Jian-Guang Lou, Dongmei Zhang

This paper presents a novel approach to translating natural language questions to SQL queries for given tables, which meets three requirements as a real-world data analysis application: cross-domain, multilingualism and enabling quick-start.

Semantic Parsing

A Split-and-Recombine Approach for Follow-up Query Analysis

1 code implementation IJCNLP 2019 Qian Liu, Bei Chen, Haoyan Liu, Lei Fang, Jian-Guang Lou, Bin Zhou, Dongmei Zhang

To leverage the advances in context-independent semantic parsing, we propose to perform follow-up query analysis, aiming to restate context-dependent natural language queries with contextual information.

Natural Language Queries Semantic Parsing

Semantic Structure Extraction for Spreadsheet Tables with a Multi-task Learning Architecture

no code implementations NeurIPS Workshop Document_Intelligen 2019 Haoyu Dong, Shijie Liu, Zhouyu Fu, Shi Han, Dongmei Zhang

To learn spatial correlations and capture semantics on spreadsheets, we have developed a novel learning-based framework for spreadsheet semantic structure extraction.

Language Modelling Multi-Task Learning

FANDA: A Novel Approach to Perform Follow-up Query Analysis

1 code implementation24 Jan 2019 Qian Liu, Bei Chen, Jian-Guang Lou, Ge Jin, Dongmei Zhang

NLIDB allow users to search databases using natural language instead of SQL-like query languages.

DeepAM: Migrate APIs with Multi-modal Sequence to Sequence Learning

no code implementations25 Apr 2017 Xiaodong Gu, Hongyu Zhang, Dongmei Zhang, Sunghun Kim

They rely on the sparse availability of bilingual projects, thus producing a limited number of API mappings.

Deep API Learning

no code implementations27 May 2016 Xiaodong Gu, Hongyu Zhang, Dongmei Zhang, Sunghun Kim

We propose DeepAPI, a deep learning based approach to generate API usage sequences for a given natural language query.

Information Retrieval Language Modelling +2

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