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20242026
most citedCWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code Generation

3 citations · 5 across the 9 of their papers we have counts for

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cs.SE2024

KGym: A Platform and Dataset to Benchmark Large Language Models on Linux Kernel Crash Resolution

Alex Mathai, Chenxi Huang, Petros Maniatis +4

Large Language Models (LLMs) are consistently improving at increasingly realistic software engineering (SE) tasks. In real-world software stacks, significant SE effort is spent dev…

cs.CL2024★ 2 cited

SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning

Yangruibo Ding, Jinjun Peng, Marcus J. Min +3

Code Large Language Models (Code LLMs) have excelled at tasks like code completion but often miss deeper semantics such as execution effects and dynamic states. This paper aims to…