Cover Image

Learning to Split: A Reinforcement-Learning-Guided Splitting Heuristic for Neural Network Verification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Swisa, Maya, Katz, Guy
Format:	Preprint
Published:	2025
Subjects:	Logic in Computer Science
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Incremental Neural Network Verification via Learned Conflicts
by: Elsaleh, Raya, et al.
Published: (2026)

Neural Network Verification using Partial Multi-Neuron Relaxation
by: Shmuel, Ido, et al.
Published: (2026)

PICID: Proof-Driven Clause Learning in Neural Network Verification
by: Isac, Omri, et al.
Published: (2025)

On Improving Deep Active Learning with Formal Verification
by: Spiegelman, Jonathan, et al.
Published: (2025)

Proof Minimization in Neural Network Verification
by: Isac, Omri, et al.
Published: (2025)

Abstraction-Based Proof Production in Formal Verification of Neural Networks
by: Elboher, Yizhak Yisrael, et al.
Published: (2025)

A Certified Proof Checker for Deep Neural Network Verification in Imandra
by: Desmartin, Remi, et al.
Published: (2024)

Towards a Certified Proof Checker for Deep Neural Network Verification
by: Desmartin, Remi, et al.
Published: (2023)

A Performance Verification Methodology for Resource Allocation Heuristics
by: Goel, Saksham, et al.
Published: (2023)

Verifying the Generalization of Deep Learning to Out-of-Distribution Domains
by: Amir, Guy, et al.
Published: (2024)

Neural Network Verification is a Programming Language Challenge
by: Cordeiro, Lucas C., et al.
Published: (2025)

Time-Sensitive Importance Splitting
by: Dengler, Gabriel, et al.
Published: (2025)

Local vs. Global Interpretability: A Computational Complexity Perspective
by: Bassan, Shahaf, et al.
Published: (2024)

Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks
by: Boetius, David, et al.
Published: (2026)

Hard to Explain: On the Computational Hardness of In-Distribution Model Interpretation
by: Amir, Guy, et al.
Published: (2024)

Formal Ethical Obligations in Reinforcement Learning Agents: Verification and Policy Updates
by: Shea-Blymyer, Colin, et al.
Published: (2024)

Splitting Argumentation Frameworks with Collective Attacks and Supports
by: Berthold, Matti, et al.
Published: (2026)

Logic Gate Neural Networks are Good for Verification
by: Kresse, Fabian, et al.
Published: (2025)

Formal Mechanistic Interpretability: Automated Circuit Discovery with Provable Guarantees
by: Hadad, Itamar, et al.
Published: (2026)

Branch and Bound for Piecewise Linear Neural Network Verification
by: Bunel, Rudy, et al.
Published: (2019)

What makes an Ensemble (Un) Interpretable?
by: Bassan, Shahaf, et al.
Published: (2025)

Splitting Answer Set Programs with respect to Intensionality Statements (Extended Version)
by: Fandinno, Jorge, et al.
Published: (2025)

A Study Of Sudoku Solving Algorithms: Backtracking and Heuristic
by: Bhattarai, Apekshya, et al.
Published: (2025)

Counterexample-Guided Repair of Reinforcement Learning Systems Using Safety Critics
by: Boetius, David, et al.
Published: (2024)

Probabilistic Verification for Modular Network-on-Chip Systems (extended version)
by: Waddoups, Nick, et al.
Published: (2025)

Provably Explaining Neural Additive Models
by: Bassan, Shahaf, et al.
Published: (2026)

Set-Based Training for Neural Network Verification
by: Koller, Lukas, et al.
Published: (2024)

Quantitative Linear Logic for Neuro-Symbolic Learning and Verification
by: Flinkow, Thomas, et al.
Published: (2026)

Marabou 2.0: A Versatile Formal Analyzer of Neural Networks
by: Wu, Haoze, et al.
Published: (2024)

Mini-Batch Robustness Verification of Deep Neural Networks
by: Tzour-Shaday, Saar, et al.
Published: (2025)

User-Guided Verification of Security Protocols via Sound Animation
by: Ye, Kangfeng, et al.
Published: (2024)

A Hierarchy of Supermartingales for $ω$-Regular Verification
by: Kura, Satoshi, et al.
Published: (2025)

A Program Instrumentation Framework for Automatic Verification
by: Amilon, Jesper, et al.
Published: (2024)

Guiding Multi-agent Multi-task Reinforcement Learning by a Hierarchical Framework with Logical Reward Shaping
by: Liu, Chanjuan, et al.
Published: (2024)

VeriFlow: Modeling Distributions for Neural Network Verification
by: Zaid, Faried Abu, et al.
Published: (2024)

Hyperproperty Verification as CHC Satisfiability
by: Itzhaky, Shachar, et al.
Published: (2023)

Craig Interpolation in Program Verification
by: Rümmer, Philipp
Published: (2026)

Tools at the Frontiers of Quantitative Verification
by: Andriushchenko, Roman, et al.
Published: (2024)

Verification of Configurable SRA Systems
by: Cimatti, Alessandro, et al.
Published: (2026)

Verification of Neural Networks (Lecture Notes)
by: Bollig, Benedikt
Published: (2026)