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Weishi Wang

4 accepted papers

2024

XCodeEval: An Execution-based Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval

Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, Weishi Wang, Md Rizwan Parvez, Shafiq Joty
ACL 2024long

Recently, pre-trained large language models (LLMs) have shown impressive abilities in generating codes from natural language descriptions, repairing buggy codes, translating codes between languages, and retrieving relevant code segments. However, the evaluation of these models has often been perform…

Cited by 11Source ↗PDF ↗Scholar ↗
2023

Retrieving Multimodal Information for Augmented Generation: A Survey

Ruochen Zhao, Hailin Chen, Weishi Wang, Fangkai Jiao, Do Xuan Long, Chengwei Qin +5
EMNLP 2023long findings

As Large Language Models (LLMs) become popular, there emerged an important trend of using multimodality to augment the LLMs' generation ability, which enables LLMs to better interact with the world. However, there lacks a unified perception of at which stage and how to incorporate different modaliti…

Cited by 0Source ↗Scholar ↗
2023

Towards Low-Resource Automatic Program Repair with Meta-Learning and Pretrained Language Models

Weishi Wang, Yue Wang, Steven Hoi, Shafiq Joty
EMNLP 2023long main

Automatic program repair (APR) has gained increasing attention as an essential technique in software development to reduce manual debugging efforts and boost developers' productivity. Recent advances in deep learning (DL) based models have demonstrated promising results by learning from large-scale…

Cited by 0Source ↗Scholar ↗
2021

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

Yue Wang, Weishi Wang, Shafiq Joty, Steven C.H. Hoi
EMNLP 2021main

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-related tasks. Despite their success, most current methods either rely on an encoder-only (or decoder-only) pre-training tha…

Cited by 1707Source ↗PDF ↗code ↗Scholar ↗