Martin T. Vechev

328 papers A* 125A 15B 15C 3Misc 5Journal 144Unranked 20

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Unified Framework for LLM Watermarks. CoRR Thibaud Gloaguen, Robin Staab, Nikola Jovanovic, Martin T. Vechev
2026	J	`jnl`	CodeTaste: Can LLMs Generate Human-Level Code Refactorings? CoRR Alex Thillen, Niels Mündler, Veselin Raychev, Martin T. Vechev
2026	J	`jnl`	Evaluating AGENTS.md: Are Repository-Level Context Files Helpful for Coding Agents? CoRR Thibaud Gloaguen, Niels Mündler, Mark Niklas Müller, Veselin Raychev, Martin T. Vechev
2026	J	`jnl`	Learning Compact Boolean Networks. CoRR Shengpu Wang, Yuhao Mao, Yani Zhang, Martin T. Vechev
2026	J	`jnl`	Recovered in Translation: Efficient Pipeline for Automated Translation of Benchmarks and Datasets. CoRR Hanna Yukhymenko, Anton Alexandrov, Martin T. Vechev
2025	A*	`conf`	A Unified Approach to Routing and Cascading for LLMs. ICML Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	Adaptive Generation of Bias-Eliciting Questions for LLMs. CoRR Robin Staab, Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	AutoBaxBuilder: Bootstrapping Code Security Benchmarking. CoRR Tobias von Arx, Niels Mündler, Mark Vero, Maximilian Baader, Martin T. Vechev
2025	A*	`conf`	Automated Benchmark Generation for Repository-Level Coding Tasks. ICML Konstantinos Vergopoulos, Mark Niklas Müller, Martin T. Vechev
2025	J	`jnl`	Automated Benchmark Generation for Repository-Level Coding Tasks. CoRR Konstantinos Vergopoulos, Mark Niklas Müller, Martin T. Vechev
2025	A*	`conf`	Average Certified Radius is a Poor Metric for Randomized Smoothing. ICML Chenhao Sun, Yuhao Mao, Mark Niklas Müller, Martin T. Vechev
2025	A*	`conf`	BaxBench: Can LLMs Generate Correct and Secure Backends? ICML Mark Vero, Niels Mündler, Victor Chibotaru, Veselin Raychev, Maximilian Baader, Nikola Jovanovic, Jingxuan He, Martin T. Vechev
2025	J	`jnl`	BaxBench: Can LLMs Generate Correct and Secure Backends? CoRR Mark Vero, Niels Mündler, Victor Chibotaru, Veselin Raychev, Maximilian Baader, Nikola Jovanovic, Jingxuan He, Martin T. Vechev
2025	A*	`conf`	Black-Box Adversarial Attacks on LLM-Based Code Completion. ICML Slobodan Jenko, Niels Mündler, Jingxuan He, Mark Vero, Martin T. Vechev
2025	A*	`conf`	Black-Box Detection of Language Model Watermarks. ICLR Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev
2025	J	`jnl`	BrokenMath: A Benchmark for Sycophancy in Theorem Proving with LLMs. CoRR Ivo Petrov, Jasper Dekoninck, Martin T. Vechev
2025	A*	`conf`	CTBench: A Library and Benchmark for Certified Training. ICML Yuhao Mao, Stefan Balauca, Martin T. Vechev
2025	J	`jnl`	Constrained Decoding of Diffusion LLMs with Context-Free Grammars. CoRR Niels Mündler, Jasper Dekoninck, Martin T. Vechev
2025	A*	`conf`	Discovering Spoofing Attempts on Language Model Watermarks. ICML Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev
2025	J	`jnl`	Dual Randomized Smoothing: Beyond Global Noise Variance. CoRR Chenhao Sun, Yuhao Mao, Martin T. Vechev
2025	J	`jnl`	Fewer Weights, More Problems: A Practical Attack on LLM Pruning. CoRR Kazuki Egashira, Robin Staab, Thibaud Gloaguen, Mark Vero, Martin T. Vechev
2025	J	`jnl`	Finetuning-Activated Backdoors in LLMs. CoRR Thibaud Gloaguen, Mark Vero, Robin Staab, Martin T. Vechev
2025	A*	`conf`	GRAIN: Exact Graph Reconstruction from Gradients. ICLR Maria Drencheva, Ivo Petrov, Maximilian Baader, Dimitar Iliev Dimitrov, Martin T. Vechev
2025	J	`jnl`	GRAIN: Exact Graph Reconstruction from Gradients. CoRR Maria Drencheva, Ivo Petrov, Maximilian Baader, Dimitar I. Dimitrov, Martin T. Vechev
2025	J	`jnl`	Gaussian Loss Smoothing Enables Certified Training with Tight Convex Relaxations. Trans. Mach. Learn. Res. Stefan Balauca, Mark Niklas Müller, Yuhao Mao, Maximilian Baader, Marc Fischer, Martin T. Vechev
2025	A*	`conf`	Language Models are Advanced Anonymizers. ICLR Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
2025	J	`jnl`	MathArena: Evaluating LLMs on Uncontaminated Math Competitions. CoRR Mislav Balunovic, Jasper Dekoninck, Ivo Petrov, Nikola Jovanovic, Martin T. Vechev
2025	A*	`conf`	MathConstruct: Challenging LLM Reasoning with Constructive Proofs. ICML Mislav Balunovic, Jasper Dekoninck, Nikola Jovanovic, Ivo Petrov, Martin T. Vechev
2025	J	`jnl`	MathConstruct: Challenging LLM Reasoning with Constructive Proofs. CoRR Mislav Balunovic, Jasper Dekoninck, Nikola Jovanovic, Ivo Petrov, Martin T. Vechev
2025	A*	`conf`	Mind the Gap: A Practical Attack on GGUF Quantization. ICML Kazuki Egashira, Robin Staab, Mark Vero, Jingxuan He, Martin T. Vechev
2025	J	`jnl`	Mind the Gap: A Practical Attack on GGUF Quantization. CoRR Kazuki Egashira, Robin Staab, Mark Vero, Jingxuan He, Martin T. Vechev
2025	J	`jnl`	MixAT: Combining Continuous and Discrete Adversarial Training for LLMs. CoRR Csaba Dékány, Stefan Balauca, Robin Staab, Dimitar I. Dimitrov, Martin T. Vechev
2025	J	`jnl`	Pay Attention to the Triggers: Constructing Backdoors That Survive Distillation. CoRR Giovanni De Muri, Mark Vero, Robin Staab, Martin T. Vechev
2025	A*	`conf`	Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation. ICLR Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	Proof or Bluff? Evaluating LLMs on 2025 USA Math Olympiad. CoRR Ivo Petrov, Jasper Dekoninck, Lyuben Baltadzhiev, Maria Drencheva, Kristian Minchev, Mislav Balunovic, Nikola Jovanovic, Martin T. Vechev
2025	J	`jnl`	Robust LLM Fingerprinting via Domain-Specific Watermarks. CoRR Thibaud Gloaguen, Robin Staab, Nikola Jovanovic, Martin T. Vechev
2025	J	`jnl`	SPEAR++: Scaling Gradient Inversion via Sparsely-Used Dictionary Learning. CoRR Alexander B. Bordetsky, Dimitar I. Dimitrov, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	SoK: Data Minimization in Machine Learning. CoRR Robin Staab, Nikola Jovanovic, Kimberly Mai, Prakhar Ganesh, Martin T. Vechev, Ferdinando Fioretto, Matthew Jagielski
2025	J	`jnl`	The Open Proof Corpus: A Large-Scale Study of LLM-Generated Mathematical Proofs. CoRR Jasper Dekoninck, Ivo Petrov, Kristian Minchev, Mislav Balunovic, Martin T. Vechev, Miroslav Marinov, Maria Drencheva, Lyuba Konova, Milen Shumanov, Kaloyan Tsvetkov, Nikolay Drenchev, Lazar Todorov, Kalina Nikolova, Nikolay Georgiev, Vanesa Kalinkova, Margulan Ismoldayev
2025	J	`jnl`	ToolFuzz - Automated Agent Tool Testing. CoRR Ivan Milev, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	Towards Watermarking of Open-Source LLMs. CoRR Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev
2025	J	`jnl`	Type-Constrained Code Generation with Language Models. CoRR Niels Mündler, Jingxuan He, Hao Wang, Koushik Sen, Dawn Song, Martin T. Vechev
2025	J	`jnl`	Type-Constrained Code Generation with Language Models. Proc. ACM Program. Lang. Niels Mündler, Jingxuan He, Hao Wang, Koushik Sen, Dawn Song, Martin T. Vechev
2025	A*	`conf`	Ward: Provable RAG Dataset Inference via LLM Watermarks. ICLR Nikola Jovanovic, Robin Staab, Maximilian Baader, Martin T. Vechev
2025	J	`jnl`	Watermarking Autoregressive Image Generation. CoRR Nikola Jovanovic, Ismail Labiad, Tomás Soucek, Martin T. Vechev, Pierre Fernandez
2025	J	`jnl`	Watermarking Diffusion Language Models. CoRR Thibaud Gloaguen, Robin Staab, Nikola Jovanovic, Martin T. Vechev
2025	J	`jnl`	qblaze: An Efficient and Scalable Sparse Quantum Simulator. Proc. ACM Program. Lang. Hristo Venev, Thien Udomsrirungruang, Dimitar Dimitrov, Timon Gehr, Martin T. Vechev
2024	A*	`conf`	A Synthetic Dataset for Personal Attribute Inference. NeurIPS Hanna Yukhymenko, Robin Staab, Mark Vero, Martin T. Vechev
2024	J	`jnl`	A Synthetic Dataset for Personal Attribute Inference. CoRR Hanna Yukhymenko, Robin Staab, Mark Vero, Martin T. Vechev
2024	J	`jnl`	A Unified Approach to Routing and Cascading for LLMs. CoRR Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2024	J	`jnl`	AlphaIntegrator: Transformer Action Search for Symbolic Integration Proofs. CoRR Mert Ünsal, Timon Gehr, Martin T. Vechev
2024	J	`jnl`	Automated Classification of Model Errors on ImageNet. CoRR Momchil Peychev, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2024	J	`jnl`	Average Certified Radius is a Poor Metric for Randomized Smoothing. CoRR Chenhao Sun, Yuhao Mao, Mark Niklas Müller, Martin T. Vechev
2024	J	`jnl`	Back to the Drawing Board for Fair Representation Learning. CoRR Angéline Pouget, Nikola Jovanovic, Mark Vero, Robin Staab, Martin T. Vechev
2024	A*	`conf`	Beyond Memorization: Violating Privacy via Inference with Large Language Models. ICLR Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
2024	J	`jnl`	BgGPT 1.0: Extending English-centric LLMs to other languages. CoRR Anton Alexandrov, Veselin Raychev, Dimitar I. Dimitrov, Ce Zhang, Martin T. Vechev, Kristina Toutanova
2024	J	`jnl`	Black-Box Detection of Language Model Watermarks. CoRR Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev
2024	J	`jnl`	COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act. CoRR Philipp Guldimann, Alexander Spiridonov, Robin Staab, Nikola Jovanovic, Mark Vero, Velko Vechev, Anna Gueorguieva, Mislav Balunovic, Nikola Konstantinov, Pavol Bielik, Petar Tsankov, Martin T. Vechev
2024	J	`jnl`	CTBENCH: A Library and Benchmark for Certified Training. CoRR Yuhao Mao, Stefan Balauca, Martin T. Vechev
2024	J	`jnl`	Code Agents are State of the Art Software Testers. CoRR Niels Mündler, Mark Niklas Müller, Jingxuan He, Martin T. Vechev
2024	A*	`conf`	ConStat: Performance-Based Contamination Detection in Large Language Models. NeurIPS Jasper Dekoninck, Mark Niklas Müller, Martin T. Vechev
2024	J	`jnl`	ConStat: Performance-Based Contamination Detection in Large Language Models. CoRR Jasper Dekoninck, Mark Niklas Müller, Martin T. Vechev
2024	A*	`conf`	Controlled Text Generation via Language Model Arithmetic. ICLR Jasper Dekoninck, Marc Fischer, Luca Beurer-Kellner, Martin T. Vechev
2024	A*	`conf`	CuTS: Customizable Tabular Synthetic Data Generation. ICML Mark Vero, Mislav Balunovic, Martin T. Vechev
2024	A*	`conf`	DAGER: Exact Gradient Inversion for Large Language Models. NeurIPS Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev
2024	J	`jnl`	DAGER: Exact Gradient Inversion for Large Language Models. CoRR Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev
2024	J	`jnl`	DeepCode AI Fix: Fixing Security Vulnerabilities with Large Language Models. CoRR Berkay Berabi, Alexey Gronskiy, Veselin Raychev, Gishor Sivanrupan, Victor Chibotaru, Martin T. Vechev
2024	J	`jnl`	Discovering Clues of Spoofed LM Watermarks. CoRR Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev
2024	J	`jnl`	Evading Data Contamination Detection for Language Models is (too) Easy. CoRR Jasper Dekoninck, Mark Niklas Müller, Maximilian Baader, Marc Fischer, Martin T. Vechev
2024	A*	`conf`	Exploiting LLM Quantization. NeurIPS Kazuki Egashira, Mark Vero, Robin Staab, Jingxuan He, Martin T. Vechev
2024	J	`jnl`	Exploiting LLM Quantization. CoRR Kazuki Egashira, Mark Vero, Robin Staab, Jingxuan He, Martin T. Vechev
2024	A*	`conf`	Expressivity of ReLU-Networks under Convex Relaxations. ICLR Maximilian Baader, Mark Niklas Müller, Yuhao Mao, Martin T. Vechev
2024	A*	`conf`	From Principle to Practice: Vertical Data Minimization for Machine Learning. SP Robin Staab, Nikola Jovanovic, Mislav Balunovic, Martin T. Vechev
2024	A*	`conf`	Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation. ICML Luca Beurer-Kellner, Marc Fischer, Martin T. Vechev
2024	J	`jnl`	Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation. CoRR Luca Beurer-Kellner, Marc Fischer, Martin T. Vechev
2024	A*	`conf`	Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning. ICLR Kostadin Garov, Dimitar Iliev Dimitrov, Nikola Jovanovic, Martin T. Vechev
2024	A*	`conf`	Instruction Tuning for Secure Code Generation. ICML Jingxuan He, Mark Vero, Gabriela Krasnopolska, Martin T. Vechev
2024	J	`jnl`	Instruction Tuning for Secure Code Generation. CoRR Jingxuan He, Mark Vero, Gabriela Krasnopolska, Martin T. Vechev
2024	J	`jnl`	Large Language Models are Advanced Anonymizers. CoRR Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
2024	—	`conf`	Mitigating Catastrophic Forgetting in Language Transfer via Model Merging. EMNLP (Findings) Anton Alexandrov, Veselin Raychev, Mark Niklas Müller, Ce Zhang, Martin T. Vechev, Kristina Toutanova
2024	J	`jnl`	Mitigating Catastrophic Forgetting in Language Transfer via Model Merging. CoRR Anton Alexandrov, Veselin Raychev, Mark Niklas Müller, Ce Zhang, Martin T. Vechev, Kristina Toutanova
2024	J	`jnl`	Modular Synthesis of Efficient Quantum Uncomputation. CoRR Hristo Venev, Timon Gehr, Dimitar Dimitrov, Martin T. Vechev
2024	J	`jnl`	Modular Synthesis of Efficient Quantum Uncomputation. Proc. ACM Program. Lang. Hristo Venev, Timon Gehr, Dimitar Dimitrov, Martin T. Vechev
2024	J	`jnl`	Multi-Neuron Unleashes Expressivity of ReLU Networks Under Convex Relaxation. CoRR Yuhao Mao, Yani Zhang, Martin T. Vechev
2024	J	`jnl`	Overcoming the Paradox of Certified Training with Gaussian Smoothing. CoRR Stefan Balauca, Mark Niklas Müller, Yuhao Mao, Maximilian Baader, Marc Fischer, Martin T. Vechev
2024	J	`jnl`	Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation. CoRR Jasper Dekoninck, Maximilian Baader, Martin T. Vechev
2024	J	`jnl`	Practical Attacks against Black-box Code Completion Engines. CoRR Slobodan Jenko, Jingxuan He, Niels Mündler, Mark Vero, Martin T. Vechev
2024	A*	`conf`	Private Attribute Inference from Images with Vision-Language Models. NeurIPS Batuhan Tömekçe, Mark Vero, Robin Staab, Martin T. Vechev
2024	J	`jnl`	Private Attribute Inference from Images with Vision-Language Models. CoRR Batuhan Tömekçe, Mark Vero, Robin Staab, Martin T. Vechev
2024	A*	`conf`	Prompt Sketching for Large Language Models. ICML Luca Beurer-Kellner, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2024	J	`jnl`	Reqomp: Space-constrained Uncomputation for Quantum Circuits. Quantum Anouk Paradis, Benjamin Bichsel, Martin T. Vechev
2024	A*	`conf`	SPEAR: Exact Gradient Inversion of Batches in Federated Learning. NeurIPS Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev
2024	J	`jnl`	SPEAR: Exact Gradient Inversion of Batches in Federated Learning. CoRR Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev
2024	A*	`conf`	SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents. NeurIPS Niels Mündler, Mark Niklas Müller, Jingxuan He, Martin T. Vechev
2024	A*	`conf`	Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation. ICLR Niels Mündler, Jingxuan He, Slobodan Jenko, Martin T. Vechev
2024	J	`jnl`	Synthetiq: Fast and Versatile Quantum Circuit Synthesis. Proc. ACM Program. Lang. Anouk Paradis, Jasper Dekoninck, Benjamin Bichsel, Martin T. Vechev
2024	A*	`conf`	Understanding Certified Training with Interval Bound Propagation. ICLR Yuhao Mao, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2024	J	`jnl`	Ward: Provable RAG Dataset Inference via LLM Watermarks. CoRR Nikola Jovanovic, Robin Staab, Maximilian Baader, Martin T. Vechev
2024	A*	`conf`	Watermark Stealing in Large Language Models. ICML Nikola Jovanovic, Robin Staab, Martin T. Vechev
2024	J	`jnl`	Watermark Stealing in Large Language Models. CoRR Nikola Jovanovic, Robin Staab, Martin T. Vechev
2023	J	`jnl`	Abstract Interpretation of Fixpoint Iterators with Applications to Neural Networks. Proc. ACM Program. Lang. Mark Niklas Müller, Marc Fischer, Robin Staab, Martin T. Vechev
2023	J	`jnl`	Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation. CoRR Benjamin Bichsel, Maximilian Baader, Anouk Paradis, Martin T. Vechev
2023	J	`jnl`	Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation. Quantum Benjamin Bichsel, Anouk Paradis, Maximilian Baader, Martin T. Vechev
2023	A*	`conf`	Automated Classification of Model Errors on ImageNet. NeurIPS Momchil Peychev, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2023	J	`jnl`	Beyond Memorization: Violating Privacy Via Inference with Large Language Models. CoRR Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
2023	A*	`conf`	Certified Training: Small Boxes are All You Need. ICLR Mark Niklas Müller, Franziska Eckert, Marc Fischer, Martin T. Vechev
2023	A*	`conf`	Connecting Certified and Adversarial Training. NeurIPS Yuhao Mao, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2023	J	`jnl`	Controlled Text Generation via Language Model Arithmetic. CoRR Jasper Dekoninck, Marc Fischer, Luca Beurer-Kellner, Martin T. Vechev
2023	J	`jnl`	Controlling Large Language Models to Generate Secure and Vulnerable Code. CoRR Jingxuan He, Martin T. Vechev
2023	A*	`conf`	Efficient Certified Training and Robustness Verification of Neural ODEs. ICLR Mustafa Zeqiri, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2023	J	`jnl`	Efficient Certified Training and Robustness Verification of Neural ODEs. CoRR Mustafa Zeqiri, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2023	J	`jnl`	Expressivity of ReLU-Networks under Convex Relaxations. CoRR Maximilian Baader, Mark Niklas Müller, Yuhao Mao, Martin T. Vechev
2023	A*	`conf`	FARE: Provably Fair Representation Learning with Practical Certificates. ICML Nikola Jovanovic, Mislav Balunovic, Dimitar Iliev Dimitrov, Martin T. Vechev
2023	J	`jnl`	From Principle to Practice: Vertical Data Minimization for Machine Learning. CoRR Robin Staab, Nikola Jovanovic, Mislav Balunovic, Martin T. Vechev
2023	A*	`conf`	Group and Attack: Auditing Differential Privacy. CCS Johan Lokna, Anouk Paradis, Dimitar I. Dimitrov, Martin T. Vechev
2023	J	`jnl`	Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning. CoRR Kostadin Garov, Dimitar I. Dimitrov, Nikola Jovanovic, Martin T. Vechev
2023	A*	`conf`	Human-Guided Fair Classification for Natural Language Processing. ICLR Florian E. Dorner, Momchil Peychev, Nikola Konstantinov, Naman Goel, Elliott Ash, Martin T. Vechev
2023	A*	`conf`	Incentivizing Honesty among Competitors in Collaborative Learning and Optimization. NeurIPS Florian E. Dorner, Nikola Konstantinov, Georgi Pashaliev, Martin T. Vechev
2023	J	`jnl`	Incentivizing Honesty among Competitors in Collaborative Learning and Optimization. CoRR Florian E. Dorner, Nikola Konstantinov, Georgi Pashaliev, Martin T. Vechev
2023	A*	`conf`	Large Language Models for Code: Security Hardening and Adversarial Testing. CCS Jingxuan He, Martin T. Vechev
2023	J	`jnl`	Programmable Synthetic Tabular Data Generation. CoRR Mark Vero, Mislav Balunovic, Martin T. Vechev
2023	J	`jnl`	Prompt Sketching for Large Language Models. CoRR Luca Beurer-Kellner, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2023	J	`jnl`	Prompting Is Programming: A Query Language for Large Language Models. Proc. ACM Program. Lang. Luca Beurer-Kellner, Marc Fischer, Martin T. Vechev
2023	J	`jnl`	Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation. CoRR Niels Mündler, Jingxuan He, Slobodan Jenko, Martin T. Vechev
2023	J	`jnl`	TAPS: Connecting Certified and Adversarial Training. CoRR Yuhao Mao, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2023	A*	`conf`	TabLeak: Tabular Data Leakage in Federated Learning. ICML Mark Vero, Mislav Balunovic, Dimitar Iliev Dimitrov, Martin T. Vechev
2023	J	`jnl`	Technical Perspective: Beautiful Symbolic Abstractions for Safe and Secure Machine Learning. Commun. ACM Martin T. Vechev
2023	J	`jnl`	Understanding Certified Training with Interval Bound Propagation. CoRR Yuhao Mao, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2022	A*	`conf`	(De-)Randomized Smoothing for Decision Stump Ensembles. NeurIPS Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2022	J	`jnl`	(De-)Randomized Smoothing for Decision Stump Ensembles. CoRR Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2022	A*	`conf`	Bayesian Framework for Gradient Leakage. ICLR Mislav Balunovic, Dimitar Iliev Dimitrov, Robin Staab, Martin T. Vechev
2022	A*	`conf`	Boosting Randomized Smoothing with Variance Reduced Classifiers. ICLR Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2022	J	`jnl`	Certified Training: Small Boxes are All You Need. CoRR Mark Niklas Müller, Franziska Eckert, Marc Fischer, Martin T. Vechev
2022	A*	`conf`	Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound. ICLR Claudio Ferrari, Mark Niklas Müller, Nikola Jovanovic, Martin T. Vechev
2022	J	`jnl`	Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound. CoRR Claudio Ferrari, Mark Niklas Müller, Nikola Jovanovic, Martin T. Vechev
2022	J	`jnl`	Data Leakage in Federated Averaging. CoRR Dimitar I. Dimitrov, Mislav Balunovic, Nikola Konstantinov, Martin T. Vechev
2022	J	`jnl`	Data Leakage in Federated Averaging. Trans. Mach. Learn. Res. Dimitar Iliev Dimitrov, Mislav Balunovic, Nikola Konstantinov, Martin T. Vechev
2022	J	`jnl`	Data Leakage in Tabular Federated Learning. CoRR Mark Vero, Mislav Balunovic, Dimitar I. Dimitrov, Martin T. Vechev
2022	J	`jnl`	FARE: Provably Fair Representation Learning. CoRR Nikola Jovanovic, Mislav Balunovic, Dimitar I. Dimitrov, Martin T. Vechev
2022	A*	`conf`	Fair Normalizing Flows. ICLR Mislav Balunovic, Anian Ruoss, Martin T. Vechev
2022	B	`conf`	Fast and Optimal Sequence-to-Graph Alignment Guided by Seeds. RECOMB Pesho Ivanov, Benjamin Bichsel, Martin T. Vechev
2022	J	`jnl`	Human-Guided Fair Classification for Natural Language Processing. CoRR Florian E. Dorner, Momchil Peychev, Nikola Konstantinov, Naman Goel, Elliott Ash, Martin T. Vechev
2022	A*	`conf`	LAMP: Extracting Text from Gradients with Language Model Priors. NeurIPS Mislav Balunovic, Dimitar I. Dimitrov, Nikola Jovanovic, Martin T. Vechev
2022	J	`jnl`	LAMP: Extracting Text from Gradients with Language Model Priors. CoRR Dimitar I. Dimitrov, Mislav Balunovic, Nikola Jovanovic, Martin T. Vechev
2022	—	`conf`	Latent Space Smoothing for Individually Fair Representations. ECCV (13) Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2022	A*	`conf`	Learning to Configure Computer Networks with Neural Algorithmic Reasoning. NeurIPS Luca Beurer-Kellner, Martin T. Vechev, Laurent Vanbever, Petar Velickovic
2022	J	`jnl`	Learning to Configure Computer Networks with Neural Algorithmic Reasoning. CoRR Luca Beurer-Kellner, Martin T. Vechev, Laurent Vanbever, Petar Velickovic
2022	A*	`conf`	On Distribution Shift in Learning-based Bug Detectors. ICML Jingxuan He, Luca Beurer-Kellner, Martin T. Vechev
2022	J	`jnl`	On Distribution Shift in Learning-based Bug Detectors. CoRR Jingxuan He, Luca Beurer-Kellner, Martin T. Vechev
2022	J	`jnl`	On the Paradox of Certified Training. Trans. Mach. Learn. Res. Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2022	J	`jnl`	PRIMA: general and precise neural network certification via scalable convex hull approximations. Proc. ACM Program. Lang. Mark Niklas Müller, Gleb Makarchuk, Gagandeep Singh, Markus Püschel, Martin T. Vechev
2022	A*	`conf`	Private and Reliable Neural Network Inference. CCS Nikola Jovanovic, Marc Fischer, Samuel Steffen, Martin T. Vechev
2022	J	`jnl`	Private and Reliable Neural Network Inference. CoRR Nikola Jovanovic, Marc Fischer, Samuel Steffen, Martin T. Vechev
2022	J	`jnl`	Prompting Is Programming: A Query Language For Large Language Models. CoRR Luca Beurer-Kellner, Marc Fischer, Martin T. Vechev
2022	A*	`conf`	Provably Robust Adversarial Examples. ICLR Dimitar Iliev Dimitrov, Gagandeep Singh, Timon Gehr, Martin T. Vechev
2022	J	`jnl`	Robust and Accurate - Compositional Architectures for Randomized Smoothing. CoRR Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2022	—	`conf`	Shared Certificates for Neural Network Verification. CAV (1) Marc Fischer, Christian Sprecher, Dimitar I. Dimitrov, Gagandeep Singh, Martin T. Vechev
2022	J	`jnl`	The Fundamental Limits of Neural Networks for Interval Certified Robustness. Trans. Mach. Learn. Res. Matthew Mirman, Maximilian Baader, Martin T. Vechev
2022	A*	`conf`	Zapper: Smart Contracts with Data and Identity Privacy. CCS Samuel Steffen, Benjamin Bichsel, Martin T. Vechev
2022	A*	`conf`	ZeeStar: Private Smart Contracts by Homomorphic Encryption and Zero-knowledge Proofs. SP Samuel Steffen, Benjamin Bichsel, Roger Baumgartner, Martin T. Vechev
2021	A*	`conf`	Automated Discovery of Adaptive Attacks on Adversarial Defenses. NeurIPS Chengyuan Yao, Pavol Bielik, Petar Tsankov, Martin T. Vechev
2021	J	`jnl`	Automated Discovery of Adaptive Attacks on Adversarial Defenses. CoRR Chengyuan Yao, Pavol Bielik, Petar Tsankov, Martin T. Vechev
2021	J	`jnl`	Bayesian Framework for Gradient Leakage. CoRR Mislav Balunovic, Dimitar I. Dimitrov, Robin Staab, Martin T. Vechev
2021	J	`jnl`	Boosting Randomized Smoothing with Variance Reduced Classifiers. CoRR Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2021	J	`jnl`	Certified Defenses: Why Tighter Relaxations May Hurt Training? CoRR Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2021	A*	`conf`	Certify or Predict: Boosting Certified Robustness with Compositional Architectures. ICLR Mark Niklas Müller, Mislav Balunovic, Martin T. Vechev
2021	A*	`conf`	DP-Sniper: Black-Box Discovery of Differential Privacy Violations using Classifiers. SP Benjamin Bichsel, Samuel Steffen, Ilija Bogunovic, Martin T. Vechev
2021	J	`jnl`	Effective Certification of Monotone Deep Equilibrium Models. CoRR Mark Niklas Müller, Robin Staab, Marc Fischer, Martin T. Vechev
2021	A*	`conf`	Efficient Certification of Spatial Robustness. AAAI Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev
2021	J	`jnl`	Fair Normalizing Flows. CoRR Mislav Balunovic, Anian Ruoss, Martin T. Vechev
2021	A*	`conf`	Fast and precise certification of transformers. PLDI Gregory Bonaert, Dimitar I. Dimitrov, Maximilian Baader, Martin T. Vechev
2021	J	`jnl`	Latent Space Smoothing for Individually Fair Representations. CoRR Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2021	A*	`conf`	Learning to Explore Paths for Symbolic Execution. CCS Jingxuan He, Gishor Sivanrupan, Petar Tsankov, Martin T. Vechev
2021	A*	`conf`	Learning to find naming issues with big code and small supervision. PLDI Jingxuan He, Cheng-Chun Lee, Veselin Raychev, Martin T. Vechev
2021	Misc	`conf`	Metha: Network Verifiers Need To Be Correct Too! NSDI Rüdiger Birkner, Tobias Brodmann, Petar Tsankov, Laurent Vanbever, Martin T. Vechev
2021	A*	`conf`	PODS: Policy Optimization via Differentiable Simulation. ICML Miguel Zamora, Momchil Peychev, Sehoon Ha, Martin T. Vechev, Stelian Coros
2021	J	`jnl`	Precise Multi-Neuron Abstractions for Neural Network Certification. CoRR Mark Niklas Müller, Gleb Makarchuk, Gagandeep Singh, Markus Püschel, Martin T. Vechev
2021	A*	`conf`	Robustness Certification for Point Cloud Models. ICCV Tobias Lorenz, Anian Ruoss, Mislav Balunovic, Gagandeep Singh, Martin T. Vechev
2021	J	`jnl`	Robustness Certification for Point Cloud Models. CoRR Tobias Lorenz, Anian Ruoss, Mislav Balunovic, Gagandeep Singh, Martin T. Vechev
2021	A*	`conf`	Robustness certification with generative models. PLDI Matthew Mirman, Alexander Hägele, Pavol Bielik, Timon Gehr, Martin T. Vechev
2021	A*	`conf`	Scalable Certified Segmentation via Randomized Smoothing. ICML Marc Fischer, Maximilian Baader, Martin T. Vechev
2021	J	`jnl`	Scalable Certified Segmentation via Randomized Smoothing. CoRR Marc Fischer, Maximilian Baader, Martin T. Vechev
2021	—	`conf`	Scalable Polyhedral Verification of Recurrent Neural Networks. CAV (1) Wonryong Ryou, Jiayu Chen, Mislav Balunovic, Gagandeep Singh, Andrei Marian Dan, Martin T. Vechev
2021	—	`conf`	Scaling Polyhedral Neural Network Verification on GPUs. MLSys Christoph Müller, François Serre, Gagandeep Singh, Markus Püschel, Martin T. Vechev
2021	J	`jnl`	Shared Certificates for Neural Network Verification. CoRR Christian Sprecher, Marc Fischer, Dimitar I. Dimitrov, Gagandeep Singh, Martin T. Vechev
2021	A*	`conf`	TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer. ICML Berkay Berabi, Jingxuan He, Veselin Raychev, Martin T. Vechev
2021	J	`jnl`	The Fundamental Limits of Interval Arithmetic for Neural Networks. CoRR Matthew Mirman, Maximilian Baader, Martin T. Vechev
2021	A*	`conf`	Unqomp: synthesizing uncomputation in Quantum circuits. PLDI Anouk Paradis, Benjamin Bichsel, Samuel Steffen, Martin T. Vechev
2020	B	`conf`	AStarix: Fast and Optimal Sequence-to-Graph Alignment. RECOMB Pesho Ivanov, Benjamin Bichsel, Harun Mustafa, André Kahles, Gunnar Rätsch, Martin T. Vechev
2020	A*	`conf`	Adversarial Attacks on Probabilistic Autoregressive Forecasting Models. ICML Raphaël Dang-Nhu, Gagandeep Singh, Pavol Bielik, Martin T. Vechev
2020	J	`jnl`	Adversarial Attacks on Probabilistic Autoregressive Forecasting Models. CoRR Raphaël Dang-Nhu, Gagandeep Singh, Pavol Bielik, Martin T. Vechev
2020	A*	`conf`	Adversarial Robustness for Code. ICML Pavol Bielik, Martin T. Vechev
2020	J	`jnl`	Adversarial Robustness for Code. CoRR Pavol Bielik, Martin T. Vechev
2020	A*	`conf`	Adversarial Training and Provable Defenses: Bridging the Gap. ICLR Mislav Balunovic, Martin T. Vechev
2020	J	`jnl`	Certification of Semantic Perturbations via Randomized Smoothing. CoRR Marc Fischer, Maximilian Baader, Martin T. Vechev
2020	A*	`conf`	Certified Defense to Image Transformations via Randomized Smoothing. NeurIPS Marc Fischer, Maximilian Baader, Martin T. Vechev
2020	Misc	`conf`	Config2Spec: Mining Network Specifications from Network Configurations. NSDI Rüdiger Birkner, Dana Drachsler-Cohen, Laurent Vanbever, Martin T. Vechev
2020	J	`jnl`	Efficient Certification of Spatial Robustness. CoRR Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev
2020	J	`jnl`	Fast and Effective Robustness Certification for Recurrent Neural Networks. CoRR Wonryong Ryou, Jiayu Chen, Mislav Balunovic, Gagandeep Singh, Andrei Marian Dan, Martin T. Vechev
2020	A*	`conf`	Guiding Program Synthesis by Learning to Generate Examples. ICLR Larissa Laich, Pavol Bielik, Martin T. Vechev
2020	A*	`conf`	Learning Certified Individually Fair Representations. NeurIPS Anian Ruoss, Mislav Balunovic, Marc Fischer, Martin T. Vechev
2020	J	`jnl`	Learning Certified Individually Fair Representations. CoRR Anian Ruoss, Mislav Balunovic, Marc Fischer, Martin T. Vechev
2020	A*	`conf`	Learning fast and precise numerical analysis. PLDI Jingxuan He, Gagandeep Singh, Markus Püschel, Martin T. Vechev
2020	J	`jnl`	Neural Network Robustness Verification on GPUs. CoRR Christoph Müller, Gagandeep Singh, Markus Püschel, Martin T. Vechev
2020	A*	`conf`	Probabilistic Verification of Network Configurations. SIGCOMM Samuel Steffen, Timon Gehr, Petar Tsankov, Laurent Vanbever, Martin T. Vechev
2020	J	`jnl`	Robustness Certification of Generative Models. CoRR Matthew Mirman, Timon Gehr, Martin T. Vechev
2020	J	`jnl`	Scalable Inference of Symbolic Adversarial Examples. CoRR Dimitar I. Dimitrov, Gagandeep Singh, Timon Gehr, Martin T. Vechev
2020	A*	`conf`	Silq: a high-level quantum language with safe uncomputation and intuitive semantics. PLDI Benjamin Bichsel, Maximilian Baader, Timon Gehr, Martin T. Vechev
2020	A*	`conf`	Universal Approximation with Certified Networks. ICLR Maximilian Baader, Matthew Mirman, Martin T. Vechev
2020	A*	`conf`	VerX: Safety Verification of Smart Contracts. SP Anton Permenev, Dimitar Dimitrov, Petar Tsankov, Dana Drachsler-Cohen, Martin T. Vechev
2020	J	`jnl`	zkay v0.2: Practical Data Privacy for Smart Contracts. CoRR Nick Baumann, Samuel Steffen, Benjamin Bichsel, Petar Tsankov, Martin T. Vechev
2020	A*	`conf`	λPSI: exact inference for higher-order probabilistic programs. PLDI Timon Gehr, Samuel Steffen, Martin T. Vechev
2019	J	`jnl`	A Provable Defense for Deep Residual Networks. CoRR Matthew Mirman, Gagandeep Singh, Martin T. Vechev
2019	J	`jnl`	An abstract domain for certifying neural networks. Proc. ACM Program. Lang. Gagandeep Singh, Timon Gehr, Markus Püschel, Martin T. Vechev
2019	A*	`conf`	Beyond the Single Neuron Convex Barrier for Neural Network Certification. NeurIPS Gagandeep Singh, Rupanshu Ganvir, Markus Püschel, Martin T. Vechev
2019	—	`conf`	Boosting Robustness Certification of Neural Networks. ICLR (Poster) Gagandeep Singh, Timon Gehr, Markus Püschel, Martin T. Vechev
2019	A*	`conf`	Certifying Geometric Robustness of Neural Networks. NeurIPS Mislav Balunovic, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin T. Vechev
2019	A*	`conf`	DL2: Training and Querying Neural Networks with Logic. ICML Marc Fischer, Mislav Balunovic, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, Martin T. Vechev
2019	A*	`conf`	Learning to Fuzz from Symbolic Execution with Application to Smart Contracts. CCS Jingxuan He, Mislav Balunovic, Nodar Ambroladze, Petar Tsankov, Martin T. Vechev
2019	J	`jnl`	Learning to Infer User Interface Attributes from Images. CoRR Philippe Schlattner, Pavol Bielik, Martin T. Vechev
2019	J	`jnl`	Online Robustness Training for Deep Reinforcement Learning. CoRR Marc Fischer, Matthew Mirman, Steven Stalder, Martin T. Vechev
2019	J	`jnl`	Predicting program properties from 'big code'. Commun. ACM Veselin Raychev, Martin T. Vechev, Andreas Krause
2019	A*	`conf`	Scalable taint specification inference with big code. PLDI Victor Chibotaru, Benjamin Bichsel, Veselin Raychev, Martin T. Vechev
2019	J	`jnl`	Universal Approximation with Certified Networks. CoRR Maximilian Baader, Matthew Mirman, Martin T. Vechev
2019	A*	`conf`	Unsupervised learning of API aliasing specifications. PLDI Jan Eberhardt, Samuel Steffen, Veselin Raychev, Martin T. Vechev
2019	A*	`conf`	zkay: Specifying and Enforcing Data Privacy in Smart Contracts. CCS Samuel Steffen, Benjamin Bichsel, Mario Gersbach, Noa Melchior, Petar Tsankov, Martin T. Vechev
2018	J	`jnl`	A practical construction for decomposing numerical abstract domains. Proc. ACM Program. Lang. Gagandeep Singh, Markus Püschel, Martin T. Vechev
2018	A*	`conf`	AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation. IEEE Symposium on Security and Privacy Timon Gehr, Matthew Mirman, Dana Drachsler-Cohen, Petar Tsankov, Swarat Chaudhuri, Martin T. Vechev
2018	B	`conf`	Automatic Verification of RMA Programs via Abstraction Extrapolation. VMCAI Cedric Baumann, Andrei Marian Dan, Yuri Meshman, Torsten Hoefler, Martin T. Vechev
2018	A*	`conf`	Bayonet: probabilistic inference for networks. PLDI Timon Gehr, Sasa Misailovic, Petar Tsankov, Laurent Vanbever, Pascal Wiesmann, Martin T. Vechev
2018	A*	`conf`	DP-Finder: Finding Differential Privacy Violations by Sampling and Optimization. CCS Benjamin Bichsel, Timon Gehr, Dana Drachsler-Cohen, Petar Tsankov, Martin T. Vechev
2018	A*	`conf`	Debin: Predicting Debug Information in Stripped Binaries. CCS Jingxuan He, Pesho Ivanov, Petar Tsankov, Veselin Raychev, Martin T. Vechev
2018	A*	`conf`	Differentiable Abstract Interpretation for Provably Robust Neural Networks. ICML Matthew Mirman, Timon Gehr, Martin T. Vechev
2018	—	`conf`	Fast Numerical Program Analysis with Reinforcement Learning. CAV (1) Gagandeep Singh, Markus Püschel, Martin T. Vechev
2018	A*	`conf`	Fast and Effective Robustness Certification. NeurIPS Gagandeep Singh, Timon Gehr, Matthew Mirman, Markus Püschel, Martin T. Vechev
2018	A	`conf`	Fine-Grained Semantics for Probabilistic Programs. ESOP Benjamin Bichsel, Timon Gehr, Martin T. Vechev
2018	A*	`conf`	Incremental inference for probabilistic programs. PLDI Marco F. Cusumano-Towner, Benjamin Bichsel, Timon Gehr, Martin T. Vechev, Vikash K. Mansinghka
2018	A*	`conf`	Inferring crypto API rules from code changes. PLDI Rumen Paletov, Petar Tsankov, Veselin Raychev, Martin T. Vechev
2018	A*	`conf`	Learning to Solve SMT Formulas. NeurIPS Mislav Balunovic, Pavol Bielik, Martin T. Vechev
2018	Misc	`conf`	Net2Text: Query-Guided Summarization of Network Forwarding Behaviors. NSDI Rüdiger Birkner, Dana Drachsler-Cohen, Laurent Vanbever, Martin T. Vechev
2018	Misc	`conf`	NetComplete: Practical Network-Wide Configuration Synthesis with Autocompletion. NSDI Ahmed El-Hassany, Petar Tsankov, Laurent Vanbever, Martin T. Vechev
2018	A*	`conf`	NetHide: Secure and Practical Network Topology Obfuscation. USENIX Security Symposium Roland Meier, Petar Tsankov, Vincent Lenders, Laurent Vanbever, Martin T. Vechev
2018	B	`conf`	Practical concurrent traversals in search trees. PPoPP Dana Drachsler-Cohen, Martin T. Vechev, Eran Yahav
2018	J	`jnl`	Race Detection in Two Dimensions. ACM Trans. Parallel Comput. Dimitar Dimitrov, Martin T. Vechev, Vivek Sarkar
2018	J	`jnl`	Robust relational layout synthesis from examples for Android. Proc. ACM Program. Lang. Pavol Bielik, Marc Fischer, Martin T. Vechev
2018	A*	`conf`	Securify: Practical Security Analysis of Smart Contracts. CCS Petar Tsankov, Andrei Marian Dan, Dana Drachsler-Cohen, Arthur Gervais, Florian Bünzli, Martin T. Vechev
2018	J	`jnl`	Securify: Practical Security Analysis of Smart Contracts. CoRR Petar Tsankov, Andrei Marian Dan, Dana Drachsler-Cohen, Arthur Gervais, Florian Buenzli, Martin T. Vechev
2018	A*	`conf`	Static serializability analysis for causal consistency. PLDI Lucas Brutschy, Dimitar Dimitrov, Peter Müller, Martin T. Vechev
2018	A*	`conf`	Training Neural Machines with Trace-Based Supervision. ICML Matthew Mirman, Dimitar Dimitrov, Pavle Djordjevic, Timon Gehr, Martin T. Vechev
2017	—	`conf`	BigBug: Practical Concurrency Analysis for SDN. SOSR Roman May, Ahmed El-Hassany, Laurent Vanbever, Martin T. Vechev
2017	J	`jnl`	Effective abstractions for verification under relaxed memory models. Comput. Lang. Syst. Struct. Andrei Marian Dan, Yuri Meshman, Martin T. Vechev, Eran Yahav
2017	A*	`conf`	Fast polyhedra abstract domain. POPL Gagandeep Singh, Markus Püschel, Martin T. Vechev
2017	—	`conf`	Finding Fix Locations for CFL-Reachability Analyses via Minimum Cuts. CAV (2) Andrei Marian Dan, Manu Sridharan, Satish Chandra, Jean-Baptiste Jeannin, Martin T. Vechev
2017	A*	`conf`	Learning Disjunctions of Predicates. COLT Nader H. Bshouty, Dana Drachsler-Cohen, Martin T. Vechev, Eran Yahav
2017	J	`jnl`	Learning Disjunctions of Predicates. CoRR Nader H. Bshouty, Dana Drachsler-Cohen, Martin T. Vechev, Eran Yahav
2017	—	`conf`	Learning a Static Analyzer from Data. CAV (1) Pavol Bielik, Veselin Raychev, Martin T. Vechev
2017	—	`conf`	Network-Wide Configuration Synthesis. CAV (2) Ahmed El-Hassany, Petar Tsankov, Laurent Vanbever, Martin T. Vechev
2017	A*	`ed.`	Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2017, Barcelona, Spain, June 18-23, 2017 PLDI Albert Cohen, Martin T. Vechev
2017	—	`conf`	Program Synthesis for Character Level Language Modeling. ICLR (Poster) Pavol Bielik, Veselin Raychev, Martin T. Vechev
2017	A*	`conf`	Serializability for eventual consistency: criterion, analysis, and applications. POPL Lucas Brutschy, Dimitar Dimitrov, Peter Müller, Martin T. Vechev
2017	A*	`conf`	Synthesis of Probabilistic Privacy Enforcement. CCS Martin Kucera, Petar Tsankov, Timon Gehr, Marco Guarnieri, Martin T. Vechev
2016	A	`conf`	FASE: functionality-aware security enforcement. ACSAC Petar Tsankov, Marco Pistoia, Omer Tripp, Martin T. Vechev, Pietro Ferrara
2016	J	`jnl`	Learning a Static Analyzer from Data. CoRR Pavol Bielik, Veselin Raychev, Martin T. Vechev
2016	A*	`conf`	Learning programs from noisy data. POPL Veselin Raychev, Pavol Bielik, Martin T. Vechev, Andreas Krause
2016	A	`conf`	Modeling and analysis of remote memory access programming. OOPSLA Andrei Marian Dan, Patrick Lam, Torsten Hoefler, Martin T. Vechev
2016	J	`jnl`	Network-wide Configuration Synthesis. CoRR Ahmed El-Hassany, Petar Tsankov, Laurent Vanbever, Martin T. Vechev
2016	J	`jnl`	Optimal Learning of Specifications from Examples. CoRR Dana Drachsler-Cohen, Martin T. Vechev, Eran Yahav
2016	A*	`conf`	PHOG: Probabilistic Model for Code. ICML Pavol Bielik, Veselin Raychev, Martin T. Vechev
2016	—	`conf`	PSI: Exact Symbolic Inference for Probabilistic Programs. CAV (1) Timon Gehr, Sasa Misailovic, Martin T. Vechev
2016	A	`conf`	Probabilistic model for code with decision trees. OOPSLA Veselin Raychev, Pavol Bielik, Martin T. Vechev
2016	J	`jnl`	Programming with "Big Code". Found. Trends Program. Lang. Martin T. Vechev, Eran Yahav
2016	A*	`conf`	SDNRacer: concurrency analysis for software-defined networks. PLDI Ahmed El-Hassany, Jeremie Miserez, Pavol Bielik, Laurent Vanbever, Martin T. Vechev
2016	A*	`conf`	Statistical Deobfuscation of Android Applications. CCS Benjamin Bichsel, Veselin Raychev, Petar Tsankov, Martin T. Vechev
2015	A*	`conf`	An Interactive System for Data Structure Development. CHI Jibin Ou, Martin T. Vechev, Otmar Hilliges
2015	B	`conf`	Effective Abstractions for Verification under Relaxed Memory Models. VMCAI Andrei Marian Dan, Yuri Meshman, Martin T. Vechev, Eran Yahav
2015	—	`conf`	Learning Commutativity Specifications. CAV (1) Timon Gehr, Dimitar Dimitrov, Martin T. Vechev
2015	A*	`conf`	Making numerical program analysis fast. PLDI Gagandeep Singh, Markus Püschel, Martin T. Vechev
2015	A*	`conf`	Predicting Program Properties from "Big Code". POPL Veselin Raychev, Martin T. Vechev, Andreas Krause
2015	J	`jnl`	Programming with "Big Code" (Dagstuhl Seminar 15472). Dagstuhl Reports William W. Cohen, Charles Sutton, Martin T. Vechev
2015	—	`conf`	Programming with "Big Code": Lessons, Techniques and Applications. SNAPL Pavol Bielik, Veselin Raychev, Martin T. Vechev
2015	B	`conf`	Race Detection in Two Dimensions. SPAA Dimitar Dimitrov, Martin T. Vechev, Vivek Sarkar
2015	—	`conf`	SDNRacer: detecting concurrency violations in software-defined networks. SOSR Jeremie Miserez, Pavol Bielik, Ahmed El-Hassany, Laurent Vanbever, Martin T. Vechev
2015	A	`conf`	Scalable race detection for Android applications. OOPSLA Pavol Bielik, Veselin Raychev, Martin T. Vechev
2015	A	`conf`	Stateless model checking of event-driven applications. OOPSLA Casper Svenning Jensen, Anders Møller, Veselin Raychev, Dimitar Dimitrov, Martin T. Vechev
2014	A*	`conf`	Code completion with statistical language models. PLDI Veselin Raychev, Martin T. Vechev, Eran Yahav
2014	A*	`conf`	Commutativity race detection. PLDI Dimitar Dimitrov, Veselin Raychev, Martin T. Vechev, Eric Koskinen
2014	—	`conf`	Phrase-Based Statistical Translation of Programming Languages. Onward! Svetoslav Karaivanov, Veselin Raychev, Martin T. Vechev
2014	B	`conf`	Practical concurrent binary search trees via logical ordering. PPoPP Dana Drachsler, Martin T. Vechev, Eran Yahav
2014	B	`conf`	Synthesis of Memory Fences via Refinement Propagation. SAS Yuri Meshman, Andrei Marian Dan, Martin T. Vechev, Eran Yahav
2014	A	`conf`	Verifying atomicity via data independence. ISSTA Ohad Shacham, Eran Yahav, Guy Golan-Gueta, Alex Aiken, Nathan Grasso Bronson, Mooly Sagiv, Martin T. Vechev
2013	J	`jnl`	Abstraction-guided synthesis of synchronization. Int. J. Softw. Tools Technol. Transf. Martin T. Vechev, Eran Yahav, Greta Yorsh
2013	B	`conf`	Automatic Synthesis of Deterministic Concurrency. SAS Veselin Raychev, Martin T. Vechev, Eran Yahav
2013	A	`conf`	Effective race detection for event-driven programs. OOPSLA Veselin Raychev, Martin T. Vechev, Manu Sridharan
2013	B	`conf`	Predicate Abstraction for Relaxed Memory Models. SAS Andrei Marian Dan, Yuri Meshman, Martin T. Vechev, Eran Yahav
2013	A	`conf`	Refactoring with synthesis. OOPSLA Veselin Raychev, Max Schäfer, Manu Sridharan, Martin T. Vechev
2012	J	`jnl`	Automatic inference of memory fences. SIGACT News Michael Kuperstein, Martin T. Vechev, Eran Yahav
2012	A*	`conf`	Dynamic synthesis for relaxed memory models. PLDI Feng Liu, Nayden Nedev, Nedyalko Prisadnikov, Martin T. Vechev, Eran Yahav
2012	J	`jnl`	Efficient data race detection for async-finish parallelism. Formal Methods Syst. Des. Raghavan Raman, Jisheng Zhao, Vivek Sarkar, Martin T. Vechev, Eran Yahav
2012	C	`ed.`	International Symposium on Memory Management, ISMM '12, Beijing, China, June 15-16, 2012 ISMM Martin T. Vechev, Kathryn S. McKinley
2012	A*	`conf`	Race detection for web applications. PLDI Boris Petrov, Martin T. Vechev, Manu Sridharan, Julian Dolby
2012	A*	`conf`	Scalable and precise dynamic datarace detection for structured parallelism. PLDI Raghavan Raman, Jisheng Zhao, Vivek Sarkar, Martin T. Vechev, Eran Yahav
2011	A	`conf`	Asynchronous assertions. OOPSLA Edward Aftandilian, Samuel Z. Guyer, Martin T. Vechev, Eran Yahav
2011	A*	`conf`	Laws of order: expensive synchronization in concurrent algorithms cannot be eliminated. POPL Hagit Attiya, Rachid Guerraoui, Danny Hendler, Petr Kuznetsov, Maged M. Michael, Martin T. Vechev
2011	A*	`conf`	Partial-coherence abstractions for relaxed memory models. PLDI Michael Kuperstein, Martin T. Vechev, Eran Yahav
2011	J	`jnl`	QVM: An Efficient Runtime for Detecting Defects in Deployed Systems. ACM Trans. Softw. Eng. Methodol. Matthew Arnold, Martin T. Vechev, Eran Yahav
2011	A	`conf`	Sprint: speculative prefetching of remote data. OOPSLA Arun Raman, Greta Yorsh, Martin T. Vechev, Eran Yahav
2011	A	`conf`	Testing atomicity of composed concurrent operations. OOPSLA Ohad Shacham, Nathan Grasso Bronson, Alex Aiken, Mooly Sagiv, Martin T. Vechev, Eran Yahav
2010	A*	`conf`	Abstraction-guided synthesis of synchronization. POPL Martin T. Vechev, Eran Yahav, Greta Yorsh
2010	B	`conf`	Automatic Verification of Determinism for Structured Parallel Programs. SAS Martin T. Vechev, Eran Yahav, Raghavan Raman, Vivek Sarkar
2010	B	`conf`	Automatic inference of memory fences. FMCAD Michael Kuperstein, Martin T. Vechev, Eran Yahav
2010	—	`conf`	Computer-aided construction of concurrent systems. CompSysTech Martin T. Vechev
2010	B	`conf`	Efficient Data Race Detection for Async-Finish Parallelism. RV Raghavan Raman, Jisheng Zhao, Vivek Sarkar, Martin T. Vechev, Eran Yahav
2010	C	`conf`	PHALANX: parallel checking of expressive heap assertions. ISMM Martin T. Vechev, Eran Yahav, Greta Yorsh
2010	A*	`conf`	Verifying linearizability with hindsight. PODC Peter W. O'Hearn, Noam Rinetzky, Martin T. Vechev, Eran Yahav, Greta Yorsh
2009	A*	`conf`	Chameleon: adaptive selection of collections. PLDI Ohad Shacham, Martin T. Vechev, Eran Yahav
2009	—	`conf`	Experience with Model Checking Linearizability. SPIN Martin T. Vechev, Eran Yahav, Greta Yorsh
2009	B	`conf`	Idempotent work stealing. PPoPP Maged M. Michael, Martin T. Vechev, Vijay A. Saraswat
2009	A	`conf`	Inferring Synchronization under Limited Observability. TACAS Martin T. Vechev, Eran Yahav, Greta Yorsh
2008	A*	`conf`	Deriving linearizable fine-grained concurrent objects. PLDI Martin T. Vechev, Eran Yahav
2008	A	`conf`	QVM: an efficient runtime for detecting defects in deployed systems. OOPSLA Matthew Arnold, Martin T. Vechev, Eran Yahav
2007	A*	`conf`	CGCExplorer: a semi-automated search procedure for provably correct concurrent collectors. PLDI Martin T. Vechev, Eran Yahav, David F. Bacon, Noam Rinetzky
2007	—	`—`	Derivation and evaluation of concurrent collectors. Martin T. Vechev
2006	A*	`conf`	Correctness-preserving derivation of concurrent garbage collection algorithms. PLDI Martin T. Vechev, Eran Yahav, David F. Bacon
2005	A	`conf`	Derivation and Evaluation of Concurrent Collectors. ECOOP Martin T. Vechev, David F. Bacon, Perry Cheng, David Grove
2005	Misc	`conf`	High-level real-time programming in Java. EMSOFT David F. Bacon, Perry Cheng, David Grove, Michael Hind, V. T. Rajan, Eran Yahav, Matthias Hauswirth, Christoph M. Kirsch, Daniel Spoonhower, Martin T. Vechev
2005	B	`conf`	Syncopation: generational real-time garbage collection in the metronome. LCTES David F. Bacon, Perry Cheng, David Grove, Martin T. Vechev
2004	C	`conf`	Write barrier elision for concurrent garbage collectors. ISMM Martin T. Vechev, David F. Bacon
2003	—	`conf`	Class Unloading with a Concurrent Garbage Collector in an Embedded Java VM. Embedded Systems and Applications Martin T. Vechev, Peter D. Petrov