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20242026
most citedFT2Ra: A Fine-Tuning-Inspired Approach to Retrieval-Augmented Code Completion

15 citations · 15 across the 6 of their papers we have counts for

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8 papers · 1 filter

cs.SE2026

A Comprehensive Study of Implementation Bugs in Multi-modal Agents

Suwan Li, Lei Bu, Shangqing Liu +5

Multi-Modal Agents (M-agents), empowered by Large Language Models (LLMs), excel in various complex, open-world scenarios such as autonomous driving and robotics. However, their uni…

cs.SE2026

SpecSyn: LLM-based Synthesis and Refinement of Formal Specifications for Real-world Program Verification

Lezhi Ma, Shangqing Liu, Yi Li +3

Program verification is a formal technique to rigorously ensure the correctness and fault-freeness of software systems. However, constructing comprehensive interprocedural specific…

cs.SE2025

EPSO: A Caching-Based Efficient Superoptimizer for BPF Bytecode

Qian Zhu, Yuxuan Liu, Ziyuan Zhu +2

Extended Berkeley Packet Filter (eBPF) allows developers to extend Linux kernel functionality without modifying its source code. To ensure system safety, an in-kernel safety checke…

cs.SE2025

Intention is All You Need: Refining Your Code from Your Intention

Qi Guo, Xiaofei Xie, Shangqing Liu +3

Code refinement aims to enhance existing code by addressing issues, refactoring, and optimizing to improve quality and meet specific requirements. As software projects scale in siz…

cs.SE2024

SpecEval: Evaluating Code Comprehension in Large Language Models via Program Specifications

Lezhi Ma, Shangqing Liu, Lei Bu +3

Large Language models have achieved impressive performance in automated software engineering. Extensive efforts have been made to evaluate the abilities of code LLMs in various asp…

cs.SE2024

Model-Enhanced LLM-Driven VUI Testing of VPA Apps

Suwan Li, Lei Bu, Guangdong Bai +3

The flourishing ecosystem centered around voice personal assistants (VPA), such as Amazon Alexa, has led to the booming of VPA apps. The largest app market Amazon skills store, for…