LLM-based security code review is vulnerable to framing bias, with a novel iterative refinement attack achieving 100% success in reintroducing vulnerabilities across real projects.
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2 Pith papers cite this work, alongside 5 external citations. Polarity classification is still indexing.
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Develops and tests a model-based RL controller with post-training for gait in a tendon-driven soft quadruped, reporting improved efficiency and robustness over benchmarks.
citing papers explorer
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Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
LLM-based security code review is vulnerable to framing bias, with a novel iterative refinement attack achieving 100% success in reintroducing vulnerabilities across real projects.
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Optimal Gait Control for a Tendon-driven Soft Quadruped Robot by Model-based Reinforcement Learning
Develops and tests a model-based RL controller with post-training for gait in a tendon-driven soft quadruped, reporting improved efficiency and robustness over benchmarks.