SCARA introduces a four-stage pipeline using state-aware verification and constrained synthesis to remediate vulnerabilities in source-unavailable industrial software, reporting 100% precision and 88.9% success on a 15-case benchmark.
VulRepair: A T5-based automated software vulnerability repair
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VulKey reaches 31.5% repair accuracy on real C/C++ vulnerabilities by matching hierarchical expert patterns to guide LLM patch generation, beating prior baselines by 7.6%.
AdaDec improves Pass@1 accuracy of LLM code generation by up to 20.9% over greedy decoding by triggering lookahead reranking only at high-uncertainty steps on HumanEval+, MBPP+, and DevEval.
HYDRA is a hybrid model that uses heuristics plus deep embeddings and a VAE to predict latent zero-day vulnerabilities in patched functions from Chrome, Android, and ImageMagick.
citing papers explorer
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SCARA: A Semantics-Constrained Autonomous Remediation Agent for Opaque Industrial Software Vulnerabilities
SCARA introduces a four-stage pipeline using state-aware verification and constrained synthesis to remediate vulnerabilities in source-unavailable industrial software, reporting 100% precision and 88.9% success on a 15-case benchmark.
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VulKey: Automated Vulnerability Repair Guided by Domain-Specific Repair Patterns
VulKey reaches 31.5% repair accuracy on real C/C++ vulnerabilities by matching hierarchical expert patterns to guide LLM patch generation, beating prior baselines by 7.6%.
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AdaDec: A Uncertainty-Guided Lookahead Decoding Framework for LLM-Based Code Generation
AdaDec improves Pass@1 accuracy of LLM code generation by up to 20.9% over greedy decoding by triggering lookahead reranking only at high-uncertainty steps on HumanEval+, MBPP+, and DevEval.
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HYDRA: A Hybrid Heuristic-Guided Deep Representation Architecture for Predicting Latent Zero-Day Vulnerabilities in Patched Functions
HYDRA is a hybrid model that uses heuristics plus deep embeddings and a VAE to predict latent zero-day vulnerabilities in patched functions from Chrome, Android, and ImageMagick.