activity
20212024
most citedImproving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning

7 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SE2024

Uncovering LLM-Generated Code: A Zero-Shot Synthetic Code Detector via Code Rewriting

Tong Ye, Yangkai Du, Tengfei Ma +4

Large Language Models (LLMs) have demonstrated remarkable proficiency in generating code. However, the misuse of LLM-generated (synthetic) code has raised concerns in both educatio…

cs.SE2023

AdaCCD: Adaptive Semantic Contrasts Discovery Based Cross Lingual Adaptation for Code Clone Detection

Yangkai Du, Tengfei Ma, Lingfei Wu +2

Code Clone Detection, which aims to retrieve functionally similar programs from large code bases, has been attracting increasing attention. Modern software often involves a diverse…

cs.PL2023

CP-BCS: Binary Code Summarization Guided by Control Flow Graph and Pseudo Code

Tong Ye, Lingfei Wu, Tengfei Ma +5

Automatically generating function summaries for binaries is an extremely valuable but challenging task, since it involves translating the execution behavior and semantics of the lo…

cs.AI2023

Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization

Tong Ye, Lingfei Wu, Tengfei Ma +5

Automatically generating human-readable text describing the functionality of a program is the intent of source code summarization. Although neural language models achieve significa…

cs.CL2022★ 7 cited

Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning

Yangkai Du, Tengfei Ma, Lingfei Wu +4

Towards real-world information extraction scenario, research of relation extraction is advancing to document-level relation extraction(DocRE). Existing approaches for DocRE aim to…

cs.CL2021

Constructing Contrastive samples via Summarization for Text Classification with limited annotations

Yangkai Du, Tengfei Ma, Lingfei Wu +4

Contrastive Learning has emerged as a powerful representation learning method and facilitates various downstream tasks especially when supervised data is limited. How to construct…