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20152023
most citedDelving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

1k citations · 1.4k across the 43 of their papers we have counts for

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Showing cs.SEShow all

5 papers · 1 filter

cs.SE2023

How Effective are Large Language Models in Generating Software Specifications?

Danning Xie, Byungwoo Yoo, Nan Jiang +4

Software specifications are essential for many Software Engineering (SE) tasks such as bug detection and test generation. Many existing approaches are proposed to extract the speci…

cs.SE2023

Symbol Preference Aware Generative Models for Recovering Variable Names from Stripped Binary

Xiangzhe Xu, Zhuo Zhang, Zian Su +8

Decompilation aims to recover the source code form of a binary executable. It has many security applications, such as malware analysis, vulnerability detection, and code hardening.…

cs.SE2023

A Syntax-Guided Multi-Task Learning Approach for Turducken-Style Code Generation

Guang Yang, Yu Zhou, Xiang Chen +4

Due to the development of pre-trained language models, automated code generation techniques have shown great promise in recent years. However, the generated code is difficult to me…

cs.SE20232 cited

KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair

Nan Jiang, Thibaud Lutellier, Yiling Lou +3

Automated Program Repair (APR) improves software reliability by generating patches for a buggy program automatically. Recent APR techniques leverage deep learning (DL) to build mod…

cs.SE2021

PyART: Python API Recommendation in Real-Time

Xincheng He, Lei Xu, Xiangyu Zhang +3

API recommendation in real-time is challenging for dynamic languages like Python. Many existing API recommendation techniques are highly effective, but they mainly support static l…