Haoze Wu

64 papers A* 7A 3B 10Journal 36Unranked 8
YearRankTypeTitle / Venue / Authors
2026 A* conf
Cubing for Tuning.
AAAI
Haoze Wu, Clark W. Barrett, Nina Narodytska
2026 A* conf
Efficiently Computing Compact Formal Explanations.
AAAI
Min Wu, Xiaofu Li, Haoze Wu, Clark W. Barrett
2026 J jnl
Formal Synthesis of Certifiably Robust Neural Lyapunov-Barrier Certificates.
CoRR
Chengxiao Wang, Haoze Wu, Gagandeep Singh
2026 J jnl
Incremental Neural Network Verification via Learned Conflicts.
CoRR
Raya Elsaleh, Liam Davis, Haoze Wu, Guy Katz
2026 J jnl
Not All Invariants Are Equal: Curating Training Data to Accelerate Program Verification with SLMs.
CoRR
Ido Pinto, Yizhak Yisrael Elboher, Haoze Wu, Nina Narodytska, Guy Katz
2026 A* conf
Parameterized Abstract Interpretation for Transformer Verification.
AAAI
Pei Huang, Dennis Wei, Omri Isac, Haoze Wu, Min Wu, Clark W. Barrett
2026 B conf
Proof Minimization in Neural Network Verification.
VMCAI
Omri Isac, Idan Refaeli, Haoze Wu, Clark W. Barrett, Guy Katz
2026 J jnl
SpotIt+: Verification-based Text-to-SQL Evaluation with Database Constraints.
CoRR
Andrew Tremante, Yang He, Rocky Klopfenstein, Yuepeng Wang, Nina Narodytska, Haoze Wu
2025 — conf
Abstraction-Based Proof Production in Formal Verification of Neural Networks (Extended Abstract).
SAIV
Yizhak Yisrael Elboher, Omri Isac, Guy Katz, Tobias Ladner, Haoze Wu
2025 J jnl
Abstraction-Based Proof Production in Formal Verification of Neural Networks.
CoRR
Yizhak Yisrael Elboher, Omri Isac, Guy Katz, Tobias Ladner, Haoze Wu
2025 J jnl
Cubing for Tuning.
CoRR
Haoze Wu, Clark W. Barrett, Nina Narodytska
2025 — conf
Neural Network Verification is a Programming Language Challenge.
ESOP (1)
Lucas C. Cordeiro, Matthew L. Daggitt, Julien Girard-Satabin, Omri Isac, Taylor T. Johnson, Guy Katz, Ekaterina Komendantskaya, Augustin Lemesle, Edoardo Manino, Artjoms Sinkarovs, Haoze Wu
2025 J jnl
Neural Network Verification is a Programming Language Challenge.
CoRR
Lucas C. Cordeiro, Matthew L. Daggitt, Julien Girard-Satabin, Omri Isac, Taylor T. Johnson, Guy Katz, Ekaterina Komendantskaya, Augustin Lemesle, Edoardo Manino, Artjoms Sinkarovs, Haoze Wu
2025 B conf
Per-Instance Subproblem Generation for Strategy Selection in SMT.
FMCAD
Amalee Wilson, Nina Narodytska, Clark W. Barrett, Haoze Wu
2025 J jnl
Proof Minimization in Neural Network Verification.
CoRR
Omri Isac, Idan Refaeli, Haoze Wu, Clark W. Barrett, Guy Katz
2025 J jnl
Proof-Driven Clause Learning in Neural Network Verification.
CoRR
Omri Isac, Idan Refaeli, Haoze Wu, Clark W. Barrett, Guy Katz
2025 J jnl
SpotIt: Evaluating Text-to-SQL Evaluation with Formal Verification.
CoRR
Rocky Klopfenstein, Yang He, Andrew Tremante, Yuepeng Wang, Nina Narodytska, Haoze Wu
2025 J jnl
The 6th International Verification of Neural Networks Competition (VNN-COMP 2025): Summary and Results.
CoRR
Konstantin Kaulen, Tobias Ladner, Stanley Bak, Christopher Brix, Hai Duong, Thomas Flinkow, Taylor T. Johnson, Lukas Koller, Edoardo Manino, ThanhVu H. Nguyen, Haoze Wu
2024 J jnl
Better Verified Explanations with Applications to Incorrectness and Out-of-Distribution Detection.
CoRR
Min Wu, Xiaofu Li, Haoze Wu, Clark W. Barrett
2024 B conf
Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificates.
FMCAD
Udayan Mandal, Guy Amir, Haoze Wu, Ieva Daukantas, Fletcher Lee Newell, Umberto J. Ravaioli, Baoluo Meng, Michael Durling, Milan Ganai, Tobey Shim, Guy Katz, Clark W. Barrett
2024 J jnl
Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificates.
CoRR
Udayan Mandal, Guy Amir, Haoze Wu, Ieva Daukantas, Fletcher Lee Newell, Umberto J. Ravaioli, Baoluo Meng, Michael Durling, Milan Ganai, Tobey Shim, Guy Katz, Clark W. Barrett
2024 A* conf
Lemur: Integrating Large Language Models in Automated Program Verification.
ICLR
Haoze Wu, Clark W. Barrett, Nina Narodytska
2024 — conf
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks.
CAV (2)
Haoze Wu, Omri Isac, Aleksandar Zeljic, Teruhiro Tagomori, Matthew L. Daggitt, Wen Kokke, Idan Refaeli, Guy Amir, Kyle Julian, Shahaf Bassan, Pei Huang, Ori Lahav, Min Wu, Min Zhang, Ekaterina Komendantskaya, Guy Katz, Clark W. Barrett
2024 J jnl
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks.
CoRR
Haoze Wu, Omri Isac, Aleksandar Zeljic, Teruhiro Tagomori, Matthew L. Daggitt, Wen Kokke, Idan Refaeli, Guy Amir, Kyle Julian, Shahaf Bassan, Pei Huang, Ori Lahav, Min Wu, Min Zhang, Ekaterina Komendantskaya, Guy Katz, Clark W. Barrett
2024 — conf
Parallel Verification for δ-Equivalence of Neural Network Quantization.
SAIV
Pei Huang, Yuting Yang, Haoze Wu, Ieva Daukantas, Min Wu, Fuqi Jia, Clark W. Barrett
2024 J jnl
Safe and Reliable Training of Learning-Based Aerospace Controllers.
CoRR
Udayan Mandal, Guy Amir, Haoze Wu, Ieva Daukantas, Fletcher Lee Newell, Umberto J. Ravaioli, Baoluo Meng, Michael Durling, Kerianne Hobbs, Milan Ganai, Tobey Shim, Guy Katz, Clark W. Barrett
2024 J jnl
The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Results.
CoRR
Christopher Brix, Stanley Bak, Taylor T. Johnson, Haoze Wu
2024 A* conf
Towards Efficient Verification of Quantized Neural Networks.
AAAI
Pei Huang, Haoze Wu, Yuting Yang, Ieva Daukantas, Min Wu, Yedi Zhang, Clark W. Barrett
2023 A conf
Convex Bounds on the Softmax Function with Applications to Robustness Verification.
AISTATS
Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi
2023 J jnl
Convex Bounds on the Softmax Function with Applications to Robustness Verification.
CoRR
Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi
2023 J jnl
Global optimization of objective functions represented by ReLU networks.
Mach. Learn.
Christopher A. Strong, Haoze Wu, Aleksandar Zeljic, Kyle D. Julian, Guy Katz, Clark W. Barrett, Mykel J. Kochenderfer
2023 J jnl
Lemur: Integrating Large Language Models in Automated Program Verification.
CoRR
Haoze Wu, Clark W. Barrett, Nina Narodytska
2023 B conf
Lightweight Online Learning for Sets of Related Problems in Automated Reasoning.
FMCAD
Haoze Wu, Christopher Hahn, Florian Lonsing, Makai Mann, Raghuram Ramanujan, Clark W. Barrett
2023 J jnl
Lightweight Online Learning for Sets of Related Problems in Automated Reasoning.
CoRR
Haoze Wu, Christopher Hahn, Florian Lonsing, Makai Mann, Raghuram Ramanujan, Clark W. Barrett
2023 A conf
Soy: An Efficient MILP Solver for Piecewise-Affine Systems.
IROS
Haoze Wu, Min Wu, Dorsa Sadigh, Clark W. Barrett
2023 J jnl
Soy: An Efficient MILP Solver for Piecewise-Affine Systems.
CoRR
Haoze Wu, Min Wu, Dorsa Sadigh, Clark W. Barrett
2023 — conf
Toward Certified Robustness Against Real-World Distribution Shifts.
SaTML
Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett
2023 J jnl
Towards Efficient Verification of Quantized Neural Networks.
CoRR
Pei Huang, Haoze Wu, Yuting Yang, Ieva Daukantas, Min Wu, Yedi Zhang, Clark W. Barrett
2023 A* conf
VeriX: Towards Verified Explainability of Deep Neural Networks.
NeurIPS
Min Wu, Haoze Wu, Clark W. Barrett
2023 J jnl
Verifying MILP Certificates with SMT Solvers.
CoRR
Runtian Zhou, Haoze Wu, Hammurabi Mendes, Jonad Pulaj
2022 — conf
Efficient Neural Network Analysis with Sum-of-Infeasibilities.
TACAS (1)
Haoze Wu, Aleksandar Zeljic, Guy Katz, Clark W. Barrett
2022 J jnl
Efficient Neural Network Analysis with Sum-of-Infeasibilities.
CoRR
Haoze Wu, Aleksandar Zeljic, Guy Katz, Clark W. Barrett
2022 B conf
On Optimizing Back-Substitution Methods for Neural Network Verification.
FMCAD
Tom Zelazny, Haoze Wu, Clark W. Barrett, Guy Katz
2022 J jnl
On Optimizing Back-Substitution Methods for Neural Network Verification.
CoRR
Tom Zelazny, Haoze Wu, Clark W. Barrett, Guy Katz
2022 J jnl
Proof-Stitch: Proof Combination for Divide and Conquer SAT Solvers.
CoRR
Abhishek Nair, Saranyu Chattopadhyay, Haoze Wu, Alex Ozdemir, Clark W. Barrett
2022 B conf
Proof-Stitch: Proof Combination for Divide-and-Conquer SAT Solvers.
FMCAD
Abhishek Anil Nair, Saranyu Chattopadhyay, Haoze Wu, Alex Ozdemir, Clark W. Barrett
2022 J jnl
Scalable Verification of GNN-based Job Schedulers.
CoRR
Haoze Wu, Clark W. Barrett, Mahmood Sharif, Nina Narodytska, Gagandeep Singh
2022 J jnl
Scalable verification of GNN-based job schedulers.
Proc. ACM Program. Lang.
Haoze Wu, Clark W. Barrett, Mahmood Sharif, Nina Narodytska, Gagandeep Singh
2022 J jnl
Toward Certified Robustness Against Real-World Distribution Shifts.
CoRR
Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett
2022 J jnl
VeriX: Towards Verified Explainability of Deep Neural Networks.
CoRR
Min Wu, Haoze Wu, Clark W. Barrett
2021 — conf
An SMT-Based Approach for Verifying Binarized Neural Networks.
TACAS (2)
Guy Amir, Haoze Wu, Clark W. Barrett, Guy Katz
2021 B conf
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers.
SAFECOMP
Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett
2021 J jnl
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers.
CoRR
Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett
2021 B conf
SAT Solving in the Serverless Cloud.
FMCAD
Alex Ozdemir, Haoze Wu, Clark W. Barrett
2020 J jnl
An SMT-Based Approach for Verifying Binarized Neural Networks.
CoRR
Guy Amir, Haoze Wu, Clark W. Barrett, Guy Katz
2020 J jnl
Global Optimization of Objective Functions Represented by ReLU Networks.
CoRR
Christopher A. Strong, Haoze Wu, Aleksandar Zeljic, Kyle D. Julian, Guy Katz, Clark W. Barrett, Mykel J. Kochenderfer
2020 B conf
Parallelization Techniques for Verifying Neural Networks.
FMCAD
Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Kyle Julian, Ahmed Irfan, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett
2020 J jnl
Parallelization Techniques for Verifying Neural Networks.
CoRR
Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Ahmed Irfan, Kyle Julian, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett
2019 A* conf
G2SAT: Learning to Generate SAT Formulas.
NeurIPS
Jiaxuan You, Haoze Wu, Clark W. Barrett, Raghuram Ramanujan, Jure Leskovec
2019 J jnl
G2SAT: Learning to Generate SAT Formulas.
CoRR
Jiaxuan You, Haoze Wu, Clark W. Barrett, Raghuram Ramanujan, Jure Leskovec
2019 B conf
Learning to Generate Industrial SAT Instances.
SOCS
Haoze Wu, Raghuram Ramanujan
2019 — conf
The Marabou Framework for Verification and Analysis of Deep Neural Networks.
CAV (1)
Guy Katz, Derek A. Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zeljic, David L. Dill, Mykel J. Kochenderfer, Clark W. Barrett
2017 J jnl
Improve SAT-solving with Machine Learning.
CoRR
Haoze Wu
2017 A conf
Improving SAT-solving with Machine Learning.
SIGCSE
Haoze Wu