7 papers
ANSR-DT: A Neuro-Symbolic Framework for Adaptive and Explainable Digital Twins
Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez +1
Digital twins are increasingly used to monitor and optimize industrial systems, yet many existing frameworks remain difficult to interpret, slow to adapt, and limited in their abil…
ANNEAL: Adapting LLM Agents via Governed Symbolic Patch Learning
Safayat Bin Hakim, Keyan Guo, Wenkai Tan +3
LLM-based agents can recover from individual execution errors, yet they repeatedly fail on the same fault when the underlying process knowledge--operator schemas, preconditions, an…
CyberCane: Neuro-Symbolic RAG for Privacy-Preserving Phishing Detection with Formal Ontology Reasoning
Safayat Bin Hakim, Aniqa Afzal, Qi Zhao +3
Privacy-critical domains require phishing detection systems that satisfy contradictory constraints: near-zero false positives to prevent workflow disruption, transparent explanatio…
Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities
Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez +2
Cybersecurity demands both rapid pattern recognition and deliberative reasoning, yet purely neural or purely symbolic approaches each address only one side of this duality. Neuro-S…
SymRAG: Efficient Neuro-Symbolic Retrieval Through Adaptive Query Routing
Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez +1
Current Retrieval-Augmented Generation systems use uniform processing, causing inefficiency as simple queries consume resources similar to complex multi-hop tasks. We present SymRA…
Decoding Android Malware with a Fraction of Features: An Attention-Enhanced MLP-SVM Approach
Safayat Bin Hakim, Muhammad Adil, Kamal Acharya +1
The escalating sophistication of Android malware poses significant challenges to traditional detection methods, necessitating innovative approaches that can efficiently identify an…