56 citations · 126 across the 9 of their papers we have counts for
9 papers
Narration-of-Thought: Inference-Time Scaffolding for Defeasible Ethical Reasoning in Large Language Models
Patrick Cooper, Alvaro Velasquez
Standard chain-of-thought on moral dilemmas exhibits two failure modes: stakeholder collapse (the trace names at most one party with a stake in the outcome) and uncertainty suppres…
DeFAb: A Dataset for Grounded Scientific Discovery through Defeasible Abduction
Patrick Cooper, Alvaro Velasquez, Avyay Sadhu
A theory can accommodate a counterexample by adding an exception. The harder problem is deciding how far the exception should extend and which predictions should survive. We presen…
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…
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…
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…
A Survey on Symbolic Knowledge Distillation of Large Language Models
Kamal Acharya, Alvaro Velasquez, Houbing Herbert Song
This survey paper delves into the emerging and critical area of symbolic knowledge distillation in Large Language Models (LLMs). As LLMs like Generative Pre-trained Transformer-3 (…
A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence
Justus Renkhoff, Ke Feng, Marc Meier-Doernberg +2
Neurosymbolic artificial intelligence (AI) is an emerging branch of AI that combines the strengths of symbolic AI and sub-symbolic AI. A major drawback of sub-symbolic AI is that i…
Neurosymbolic Reinforcement Learning and Planning: A Survey
K. Acharya, W. Raza, C. M. J. M. Dourado +2
The area of Neurosymbolic Artificial Intelligence (Neurosymbolic AI) is rapidly developing and has become a popular research topic, encompassing sub-fields such as Neurosymbolic De…