3 papers
cs.IR2026
Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback
Md Zarif Ul Alam, Alireza Salemi, Hamed Zamani
Agentic search systems iteratively interact with retrieval models to answer complex queries. Despite substantial progress, optimizing retrievers for agentic search remains challeng…
cs.CR2026
QASecClaw: A Multi-Agent LLM Approach for False Positive Reduction in Static Application Security Testing
Mohd Ruhul Ameen, Md Takrim Ul Alam, Akif Islam
Static Application Security Testing tools help developers find security vulnerabilities before release, but they often produce many false positives. This increases manual review ef…
cs.CR2026
Prompt Control-Flow Integrity: A Priority-Aware Runtime Defense Against Prompt Injection in LLM Systems
Md Takrim Ul Alam, Akif Islam, Mohd Ruhul Ameen +2
Large language models (LLMs) deployed behind APIs and retrieval-augmented generation (RAG) stacks are vulnerable to prompt injection attacks that may override system policies, subv…