29 citations · 151 across the 18 of their papers we have counts for
18 papers
Hadamard Adapter: An Extreme Parameter-Efficient Adapter Tuning Method for Pre-trained Language Models
Yuyan Chen, Qiang Fu, Ge Fan +6
Recent years, Pre-trained Language models (PLMs) have swept into various fields of artificial intelligence and achieved great success. However, most PLMs, such as T5 and GPT3, have…
Data Transformation to Construct a Dataset for Generating Entity-Relationship Model from Natural Language
Zhenwen Li, Jian-Guang Lou, Tao Xie
In order to reduce the manual cost of designing ER models, recent approaches have been proposed to address the task of NL2ERM, i.e., automatically generating entity-relationship (E…
LayoutPrompter: Awaken the Design Ability of Large Language Models
Jiawei Lin, Jiaqi Guo, Shizhao Sun +3
Conditional graphic layout generation, which automatically maps user constraints to high-quality layouts, has attracted widespread attention today. Although recent works have achie…
A Survey for Graphic Design Intelligence
Danqing Huang, Jiaqi Guo, Shizhao Sun +6
Graphic design is an effective language for visual communication. Using complex composition of visual elements (e.g., shape, color, font) guided by design principles and aesthetics…
Re-Reading Improves Reasoning in Large Language Models
Xiaohan Xu, Chongyang Tao, Tao Shen +5
To enhance the reasoning capabilities of off-the-shelf Large Language Models (LLMs), we introduce a simple, yet general and effective prompting method, Re2, i.e., \textbf{Re}-\text…
A Parse-Then-Place Approach for Generating Graphic Layouts from Textual Descriptions
Jiawei Lin, Jiaqi Guo, Shizhao Sun +4
Creating layouts is a fundamental step in graphic design. In this work, we propose to use text as the guidance to create graphic layouts, i.e., Text-to-Layout, aiming to lower the…
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
Haipeng Luo, Qingfeng Sun, Can Xu +8
Large language models (LLMs), such as GPT-4, have shown remarkable performance in natural language processing (NLP) tasks, including challenging mathematical reasoning. However, mo…
LayoutFormer++: Conditional Graphic Layout Generation via Constraint Serialization and Decoding Space Restriction
Zhaoyun Jiang, Jiaqi Guo, Shizhao Sun +6
Conditional graphic layout generation, which generates realistic layouts according to user constraints, is a challenging task that has not been well-studied yet. First, there is li…
Revisiting Iterative Back-Translation from the Perspective of Compositional Generalization
Yinuo Guo, Hualei Zhu, Zeqi Lin +3
Human intelligence exhibits compositional generalization (i.e., the capacity to understand and produce unseen combinations of seen components), but current neural seq2seq models la…
"What Do You Mean by That?" A Parser-Independent Interactive Approach for Enhancing Text-to-SQL
Yuntao Li, Bei Chen, Qian Liu +4
In Natural Language Interfaces to Databases systems, the text-to-SQL technique allows users to query databases by using natural language questions. Though significant progress in t…
Retrieve-Then-Adapt: Example-based Automatic Generation for Proportion-related Infographics
Chunyao Qian, Shizhao Sun, Weiwei Cui +3
Infographic is a data visualization technique which combines graphic and textual descriptions in an aesthetic and effective manner. Creating infographics is a difficult and time-co…
You Impress Me: Dialogue Generation via Mutual Persona Perception
Qian Liu, Yihong Chen, Bei Chen +4
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 response…
A Split-and-Recombine Approach for Follow-up Query Analysis
Qian Liu, Bei Chen, Haoyan Liu +4
Context-dependent semantic parsing has proven to be an important yet challenging task. To leverage the advances in context-independent semantic parsing, we propose to perform follo…
Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation
Jiaqi Guo, Zecheng Zhan, Yan Gao +4
We present a neural approach called IRNet for complex and cross-domain Text-to-SQL. IRNet aims to address two challenges: 1) the mismatch between intents expressed in natural langu…
LambdaOpt: Learn to Regularize Recommender Models in Finer Levels
Yihong Chen, Bei Chen, Xiangnan He +4
Recommendation models mainly deal with categorical variables, such as user/item ID and attributes. Besides the high-cardinality issue, the interactions among such categorical varia…
FANDA: A Novel Approach to Perform Follow-up Query Analysis
Qian Liu, Bei Chen, Jian-Guang Lou +2
Recent work on Natural Language Interfaces to Databases (NLIDB) has attracted considerable attention. NLIDB allow users to search databases using natural language instead of SQL-li…
QuanFuzz: Fuzz Testing of Quantum Program
Jiyuan Wang, Ming Gao, Yu Jiang +4
Nowadays, quantum program is widely used and quickly developed. However, the absence of testing methodology restricts their quality. Different input format and operator from tradit…
Learning-to-Ask: Knowledge Acquisition via 20 Questions
Yihong Chen, Bei Chen, Xuguang Duan +4
Almost all the knowledge empowered applications rely upon accurate knowledge, which has to be either collected manually with high cost, or extracted automatically with unignorable…