Evaluations across agent systems, benchmarks, and backbone LLMs under 65 fault configurations show that all systems degrade under fault injection, suggesting that robustness depends on system implementation rather than model capability.
Gou Tan, Zhensu Sun, Jie-Ke Shi et al.· Proceedings of the 41st IEEE...· 6 citations
The first systematic study of model editing as a model-level hardening mechanism for secure code generation is conducted, evaluating 3 state-of-the-art editing methods across diverse LLM families and comparing them with CoSec, a representative inference-time approach, focusing on security, robustness, generalization, a...
Wei-Feng Sun, Quan-Jun Zhang, Yuchen Chen et al.· 0 citations
Large language models (LLMs) excel at general-purpose code generation, yet how well they handle scientific code remains an open question. Existing datasets and benchmarks are limited in scale, domain coverage, or executable verification, leaving the true gap between current LLMs and reliable scientific code generators...
Weifeng Sun, Ye Fan, Yuchen Chen et al.· arXiv.org· 0 citations
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