Haoze Wu
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
31
Venues
18
Active years
2017–2026
Best venue rank
A*
Where they publish
Papers
31 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Parameterized Abstract Interpretation for Transformer Verification. | Pei Huang, Dennis Wei, Omri Isac, Haoze Wu, Min Wu, Clark W. Barrett |
| 2026 | AAAI | Cubing for Tuning. | Haoze Wu, Clark W. Barrett, Nina Narodytska |
| 2026 | AAAI | Efficiently Computing Compact Formal Explanations. | Min Wu, Xiaofu Li, Haoze Wu, Clark W. Barrett |
| 2026 | AAAI | ReCode: Updating Code API Knowledge with Reinforcement Learning. | Haoze Wu, Yunzhi Yao, Wenhao Yu, Ningyu Zhang |
| 2026 | FAST | CoFS: A Filesystem for Fast Container Startup. | Li Wang, Jinxu Du, Yang Yang, Qingbo Wu, Tao Liu, Haoze Wu |
| 2026 | WWW | Towards Responsible Recommendations: A Daily Updated Ranking Model for Content Issue Detection. | Haoze Wu, Chenghui Yu, Bingfeng Deng, Daniel Chen |
| 2026 | VMCAI | Proof Minimization in Neural Network Verification. | Omri Isac, Idan Refaeli, Haoze Wu, Clark W. Barrett, Guy Katz |
| 2025 | ESOP | Neural Network Verification is a Programming Language Challenge. | 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 | FMCAD | Per-Instance Subproblem Generation for Strategy Selection in SMT. | Amalee Wilson, Nina Narodytska, Clark W. Barrett, Haoze Wu |
| 2025 | RecSys | Unified Survey Modeling to Limit Negative User Experiences in Recommendation Systems. | Chenghui Yu, Haoze Wu, Jian Ding, Bingfeng Deng, Hongyu Xiong |
| 2024 | AAAI | Towards Efficient Verification of Quantized Neural Networks. | Pei Huang, Haoze Wu, Yuting Yang, Ieva Daukantas, Min Wu, Yedi Zhang, Clark W. Barrett |
| 2024 | CAV | Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. | 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 | FMCAD | Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificates. | 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 | ICLR | Lemur: Integrating Large Language Models in Automated Program Verification. | Haoze Wu, Clark W. Barrett, Nina Narodytska |
| 2024 | NSDI | Efficient Exposure of Partial Failure Bugs in Distributed Systems with Inferred Abstract States. | Haoze Wu, Jia Pan, Peng Huang |
| 2024 | SOSP | Efficient Reproduction of Fault-Induced Failures in Distributed Systems with Feedback-Driven Fault Injection. | Jia Pan, Haoze Wu, Tanakorn Leesatapornwongsa, Suman Nath, Peng Huang |
| 2023 | AISTATS | Convex Bounds on the Softmax Function with Applications to Robustness Verification. | Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi |
| 2023 | FMCAD | Lightweight Online Learning for Sets of Related Problems in Automated Reasoning. | Haoze Wu, Christopher Hahn, Florian Lonsing, Makai Mann, Raghuram Ramanujan, Clark W. Barrett |
| 2023 | IROS | Soy: An Efficient MILP Solver for Piecewise-Affine Systems. | Haoze Wu, Min Wu, Dorsa Sadigh, Clark W. Barrett |
| 2022 | FMCAD | Proof-Stitch: Proof Combination for Divide-and-Conquer SAT Solvers. | Abhishek Anil Nair, Saranyu Chattopadhyay, Haoze Wu, Alex Ozdemir, Clark W. Barrett |
| 2022 | FMCAD | On Optimizing Back-Substitution Methods for Neural Network Verification. | Tom Zelazny, Haoze Wu, Clark W. Barrett, Guy Katz |
| 2022 | TACAS | Efficient Neural Network Analysis with Sum-of-Infeasibilities. | Haoze Wu, Aleksandar Zeljic, Guy Katz, Clark W. Barrett |
| 2021 | FMCAD | SAT Solving in the Serverless Cloud. | Alex Ozdemir, Haoze Wu, Clark W. Barrett |
| 2021 | SAFECOMP | DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers. | Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett |
| 2021 | TACAS | An SMT-Based Approach for Verifying Binarized Neural Networks. | Guy Amir, Haoze Wu, Clark W. Barrett, Guy Katz |
| 2020 | FMCAD | Parallelization Techniques for Verifying Neural Networks. | Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Kyle Julian, Ahmed Irfan, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett |
| 2020 | IJCAI | Multi-Scale Spatial-Temporal Integration Convolutional Tube for Human Action Recognition. | Haoze Wu, Jiawei Liu, Xierong Zhu, Meng Wang, Zheng-Jun Zha |
| 2019 | CAV | The Marabou Framework for Verification and Analysis of Deep Neural Networks. | 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 |
| 2019 | IJCAI | Mutually Reinforced Spatio-Temporal Convolutional Tube for Human Action Recognition. | Haoze Wu, Jiawei Liu, Zheng-Jun Zha, Zhenzhong Chen, Xiaoyan Sun |
| 2019 | SoCS | Learning to Generate Industrial SAT Instances. | Haoze Wu, Raghuram Ramanujan |
| 2017 | SIGCSE | Improving SAT-solving with Machine Learning. | Haoze Wu |