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Large language models (LLMs) have shown strong results in classical code generation and are increasingly used to write the unit tests that safeguard that code. Whether they can do the same for quantum software is less clear, because quantum programs are probabilistic, depend on numerical tolerances, and are judged by d...
Image-to-text jailbreaks place harmful intent in text, image content, or the relationship between them. We examine image-side factors across four published attack families on a 313-prompt StrongREJECT slice, using five multimodal models and an additional appendix evaluation of InternVL3.5-8B. The harmful instruction is...
FinHardBench, a benchmark of 33 financial computing tasks, is presented together with three experiments that mirror the real-world FPGA iteration cycle: generating new modules from specifications, tuning system-level configurations across a 6-stage trading pipeline, and adapting existing modules to specification change...
CTF-ABACUS is introduced, a trace-based agent auditing framework that reconstructs each run as an evidence-grounded solve profile that provides a basis for designing benchmarks that better isolate the offensive capabilities of autonomous language-model agents.
This paper introduces T2L (Trace-to-Line), a reproducible research framework that narrows repository-scale code into candidate vulnerable lines through AST-based chunking, structured diagnostic information collection, and evidence-guided refinement that improves trace-to-line localization.
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