Cover Image

Incompleteness of AI Safety Verification via Kolmogorov Complexity

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Hasan, Munawar
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Internalizing Safety Understanding in Large Reasoning Models via Verification
by: Zhang, Yi, et al.
Published: (2026)

Relevance for Stability of Verification Status of a Set of Arguments in Incomplete Argumentation Frameworks (with Proofs)
by: Xiong, Anshu, et al.
Published: (2025)

Why AI Safety Requires Uncertainty, Incomplete Preferences, and Non-Archimedean Utilities
by: Benavoli, Alessio, et al.
Published: (2025)

Motion-to-Response Content Generation via Multi-Agent AI System with Real-Time Safety Verification
by: Lee, HyeYoung
Published: (2026)

Empirical Validation of the Classification-Verification Dichotomy for AI Safety Gates
by: Scrivens, Arsenios
Published: (2026)

Containment Verification: AI Safety Guarantees Independent of Alignment
by: Moon, Royce, et al.
Published: (2026)

Persona Non Grata: Single-Method Safety Evaluation Is Incomplete for Persona-Imbued LLMs
by: Li, Wenkai, et al.
Published: (2026)

ThreatGPT: An Agentic AI Framework for Enhancing Public Safety through Threat Modeling
by: Zisad, Sharif Noor, et al.
Published: (2025)

Unifying Two Types of Scaling Laws from the Perspective of Conditional Kolmogorov Complexity
by: Wan, Jun
Published: (2025)

Prime Successor Irreducibility: Turing Machine Complexity, Kolmogorov Complexity, and Weakness-Based Formulations
by: Goertzel, Ben, et al.
Published: (2026)

Fact in Fragments: Deconstructing Complex Claims via LLM-based Atomic Fact Extraction and Verification
by: Zheng, Liwen, et al.
Published: (2025)

A Dynamical Systems Framework for Reinforcement Learning Safety and Robustness Verification
by: Nasir, Ahmed, et al.
Published: (2025)

Advancing Neural Network Verification through Hierarchical Safety Abstract Interpretation
by: Marzari, Luca, et al.
Published: (2025)

The Need for Verification in AI-Driven Scientific Discovery
by: Cornelio, Cristina, et al.
Published: (2025)

Saarthi: The First AI Formal Verification Engineer
by: Kumar, Aman, et al.
Published: (2025)

The Folly of AI for Age Verification
by: McIlroy-Young, Reid
Published: (2025)

The Refusal--Compliance Tradeoff: A Large-Scale Safety Behavior Audit of Large Language Models
by: Hasan, Alif Al, et al.
Published: (2026)

Abducing Compliance of Incomplete Event Logs
by: Chesani, Federico, et al.
Published: (2016)

GDPR Auto-Formalization with AI Agents and Human Verification
by: Nguyen, Ha Thanh, et al.
Published: (2026)

Agentic AI-based Coverage Closure for Formal Verification
by: Pothireddypalli, Sivaram, et al.
Published: (2026)

Generative AI Augmented Induction-based Formal Verification
by: Kumar, Aman, et al.
Published: (2024)

Information-Theoretic Limits of Safety Verification for Self-Improving Systems
by: Scrivens, Arsenios
Published: (2026)

On the Computational Complexity of Stackelberg Planning and Meta-Operator Verification: Technical Report
by: Behnke, Gregor, et al.
Published: (2024)

Complete Approximations of Incomplete Queries
by: Corman, Julien, et al.
Published: (2024)

The Incomplete Bridge: How AI Research (Mis)Engages with Psychology
by: Jiang, Han, et al.
Published: (2025)

Improving the Safety and Trustworthiness of Medical AI via Multi-Agent Evaluation Loops
by: Ghafoor, Zainab, et al.
Published: (2026)

Verification methods for international AI agreements
by: Wasil, Akash R., et al.
Published: (2024)

On AI Verification in Open RAN
by: Soundrarajan, Rahul, et al.
Published: (2025)

Preventing the Collapse of Peer Review Requires Verification-First AI
by: You, Lei, et al.
Published: (2026)

Evaluating Counterfactual Explanation Methods on Incomplete Inputs
by: Leofante, Francesco, et al.
Published: (2026)

NeuroAI for AI Safety
by: Mineault, Patrick, et al.
Published: (2024)

A Hybrid Knowledge-Grounded Framework for Safety and Traceability in Prescription Verification
by: Zhu, Yichi, et al.
Published: (2026)

Bridging Efficiency and Safety: Formal Verification of Neural Networks with Early Exits
by: Elboher, Yizhak Yisrael, et al.
Published: (2025)

TriGuard: Testing Model Safety with Attribution Entropy, Verification, and Drift
by: Mahato, Dipesh Tharu, et al.
Published: (2025)

AI Safety: A Climb To Armageddon?
by: Cappelen, Herman, et al.
Published: (2024)

A Different Approach to AI Safety: Proceedings from the Columbia Convening on Openness in Artificial Intelligence and AI Safety
by: François, Camille, et al.
Published: (2025)

CORE-Acu: Structured Reasoning Traces and Knowledge Graph Safety Verification for Acupuncture Clinical Decision Support
by: Xu, Liuyi, et al.
Published: (2026)

Are Transformers More Robust? Towards Exact Robustness Verification for Transformers
by: Liao, Brian Hsuan-Cheng, et al.
Published: (2022)

Safety by Measurement: A Systematic Literature Review of AI Safety Evaluation Methods
by: Grey, Markov, et al.
Published: (2025)

Knowledge Graphs, the Missing Link in Agentic AI-based Formal Verification
by: Viswambharan, Vaisakh Naduvodi, et al.
Published: (2026)