111 citations · 337 across the 18 of their papers we have counts for
19 papers
RAP-Gen: Retrieval-Augmented Patch Generation with CodeT5 for Automatic Program Repair
Weishi Wang, Yue Wang, Shafiq Joty +1
Automatic program repair (APR) is crucial to reduce manual debugging efforts for developers and improve software reliability. While conventional search-based techniques typically r…
Toward High Quality Facial Representation Learning
Yue Wang, Jinlong Peng, Jiangning Zhang +4
Face analysis tasks have a wide range of applications, but the universal facial representation has only been explored in a few works. In this paper, we explore high-performance pre…
MathChat: Converse to Tackle Challenging Math Problems with LLM Agents
Yiran Wu, Feiran Jia, Shaokun Zhang +7
Employing Large Language Models (LLMs) to address mathematical problems is an intriguing research endeavor, considering the abundance of math problems expressed in natural language…
CodeTF: One-stop Transformer Library for State-of-the-art Code LLMs
Nghi D. Q. Bui, Hung Le, Yue Wang +3
Code intelligence plays a key role in transforming modern software engineering. Recently, deep learning-based models, especially Transformer-based large language models (LLMs), hav…
CodeT5+: Open Code Large Language Models for Code Understanding and Generation
Yue Wang, Hung Le, Akhilesh Deepak Gotmare +3
Large language models (LLMs) pretrained on vast source code have achieved prominent progress in code intelligence. However, existing code LLMs have two main limitations in terms of…
GE-Blender: Graph-Based Knowledge Enhancement for Blender
Xiaolei Lian, Xunzhu Tang, Yue Wang
Although the great success of open-domain dialogue generation, unseen entities can have a large impact on the dialogue generation task. It leads to performance degradation of the m…
PaCaNet: A Study on CycleGAN with Transfer Learning for Diversifying Fused Chinese Painting and Calligraphy
Zuhao Yang, Huajun Bai, Zhang Luo +5
AI-Generated Content (AIGC) has recently gained a surge in popularity, powered by its high efficiency and consistency in production, and its capability of being customized and dive…
Detect-Localize-Repair: A Unified Framework for Learning to Debug with CodeT5
Nghi D. Q. Bui, Yue Wang, Steven Hoi
Automated software debugging is a crucial task for improving the productivity of software developers. Many neural-based techniques have been proven effective for debugging-related…
RPN: A Word Vector Level Data Augmentation Algorithm in Deep Learning for Language Understanding
Zhengqing Yuan, Xiaolong Zhang, Yue Wang +4
Data augmentation is a widely used technique in machine learning to improve model performance. However, existing data augmentation techniques in natural language understanding (NLU…
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning
Hung Le, Yue Wang, Akhilesh Deepak Gotmare +2
Program synthesis or code generation aims to generate a program that satisfies a problem specification. Recent approaches using large-scale pretrained language models (LMs) have sh…
CtlGAN: Few-shot Artistic Portraits Generation with Contrastive Transfer Learning
Yue Wang, Ran Yi, Luying Li +3
Generating artistic portraits is a challenging problem in computer vision. Existing portrait stylization models that generate good quality results are based on Image-to-Image Trans…
Machine Translation Verbosity Control for Automatic Dubbing
Surafel M. Lakew, Marcello Federico, Yue Wang +4
Automatic dubbing aims at seamlessly replacing the speech in a video document with synthetic speech in a different language. The task implies many challenges, one of which is gener…
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
Yue Wang, Weishi Wang, Shafiq Joty +1
Pre-trained models for Natural Languages (NL) like BERT and GPT have been recently shown to transfer well to Programming Languages (PL) and largely benefit a broad set of code-rela…
Cross-Media Keyphrase Prediction: A Unified Framework with Multi-Modality Multi-Head Attention and Image Wordings
Yue Wang, Jing Li, Michael R. Lyu +1
Social media produces large amounts of contents every day. To help users quickly capture what they need, keyphrase prediction is receiving a growing attention. Nevertheless, most p…
VD-BERT: A Unified Vision and Dialog Transformer with BERT
Yue Wang, Shafiq Joty, Michael R. Lyu +3
Visual dialog is a challenging vision-language task, where a dialog agent needs to answer a series of questions through reasoning on the image content and dialog history. Prior wor…
Topic-Aware Neural Keyphrase Generation for Social Media Language
Yue Wang, Jing Li, Hou Pong Chan +3
A huge volume of user-generated content is daily produced on social media. To facilitate automatic language understanding, we study keyphrase prediction, distilling salient informa…
Microblog Hashtag Generation via Encoding Conversation Contexts
Yue Wang, Jing Li, Irwin King +2
Automatic hashtag annotation plays an important role in content understanding for microblog posts. To date, progress made in this field has been restricted to phrase selection from…
An end-to-end Generative Retrieval Method for Sponsored Search Engine --Decoding Efficiently into a Closed Target Domain
Yijiang Lian, Zhijie Chen, Jinlong Hu +11
In this paper, we present a generative retrieval method for sponsored search engine, which uses neural machine translation (NMT) to generate keywords directly from query. This meth…
Code Completion with Neural Attention and Pointer Networks
Jian Li, Yue Wang, Michael R. Lyu +1
Intelligent code completion has become an essential research task to accelerate modern software development. To facilitate effective code completion for dynamically-typed programmi…