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Martin T. Vechev
- > Home > Persons > Martin T. Vechev
Publications
- 2024
- [i66]Jingxuan He, Mark Vero, Gabriela Krasnopolska, Martin T. Vechev:
Instruction Tuning for Secure Code Generation. CoRR abs/2402.09497 (2024) - 2023
- [c147]Jingxuan He, Martin T. Vechev:
Large Language Models for Code: Security Hardening and Adversarial Testing. CCS 2023: 1865-1879 - [i59]Jingxuan He, Martin T. Vechev:
Controlling Large Language Models to Generate Secure and Vulnerable Code. CoRR abs/2302.05319 (2023) - [i55]Niels Mündler, Jingxuan He, Slobodan Jenko, Martin T. Vechev:
Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation. CoRR abs/2305.15852 (2023) - 2022
- [c128]Jingxuan He, Luca Beurer-Kellner, Martin T. Vechev:
On Distribution Shift in Learning-based Bug Detectors. ICML 2022: 8559-8580 - [i43]Jingxuan He, Luca Beurer-Kellner, Martin T. Vechev:
On Distribution Shift in Learning-based Bug Detectors. CoRR abs/2204.10049 (2022) - 2021
- [c120]Jingxuan He, Gishor Sivanrupan, Petar Tsankov, Martin T. Vechev:
Learning to Explore Paths for Symbolic Execution. CCS 2021: 2526-2540 - [c117]Berkay Berabi, Jingxuan He, Veselin Raychev, Martin T. Vechev:
TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer. ICML 2021: 780-791 - [c110]Jingxuan He, Cheng-Chun Lee, Veselin Raychev, Martin T. Vechev:
Learning to find naming issues with big code and small supervision. PLDI 2021: 296-311 - 2020
- [c96]Jingxuan He, Gagandeep Singh, Markus Püschel, Martin T. Vechev:
Learning fast and precise numerical analysis. PLDI 2020: 1112-1127 - 2019
- [c92]Jingxuan He, Mislav Balunovic, Nodar Ambroladze, Petar Tsankov, Martin T. Vechev:
Learning to Fuzz from Symbolic Execution with Application to Smart Contracts. CCS 2019: 531-548 - 2018
- [c81]Jingxuan He, Pesho Ivanov, Petar Tsankov, Veselin Raychev, Martin T. Vechev:
Debin: Predicting Debug Information in Stripped Binaries. CCS 2018: 1667-1680
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last updated on 2024-04-07 22:27 CEST by the dblp team
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