3 papers
cs.SE2025
LLM-Driven Adaptive Source-Sink Identification and False Positive Mitigation for Static Analysis
Shiyin Lin
Static analysis is effective for discovering software vulnerabilities but notoriously suffers from incomplete source--sink specifications and excessive false positives (FPs). We pr…
cs.CL2025
Abductive Inference in Retrieval-Augmented Language Models: Generating and Validating Missing Premises
Shiyin Lin
Large Language Models (LLMs) enhanced with retrieval -- commonly referred to as Retrieval-Augmented Generation (RAG) -- have demonstrated strong performance in knowledge-intensive…
cs.CR2025
Hybrid Fuzzing with LLM-Guided Input Mutation and Semantic Feedback
Shiyin Lin
Software fuzzing has become a cornerstone in automated vulnerability discovery, yet existing mutation strategies often lack semantic awareness, leading to redundant test cases and…