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George J. Pappas

39 papers · 2018–2025 · 13 conferences · across top CS/AI conferences

Achievements

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+12 more ↓ πŸ—ΊοΈ Taxonomy Completionist (18) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (6) 🐣 Hot Topic Early Bird
🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (18) 🀝 Dynamic Duo (17) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (156) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ”₯ Unstoppable (8) ❓ The Questioner πŸ’Ž Century Club (39)

Conferences

L4DC (9) NIPS (9) ICML (7) ICLR (3) IJCAI (2) RSS (2) AAAI (1) AACL (1) AISTATS (1) COLT (1) CORL (1) IJCNLP (1) JMLR (1)

Research topics

Papers

Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing IJCNLP 2025 Distilling On-device Language Models for Robot Planning with Minimal Human Intervention CORL 2025 Adversarial Reasoning at Jailbreaking Time ICML 2025 Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing AACL 2025 Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents ICML 2025 CViT: Continuous Vision Transformer for Operator Learning ICLR 2025 Domain Randomization is Sample Efficient for Linear Quadratic Control L4DC 2025 Adversarial Training Should Be Cast as a Non-Zero-Sum Game ICLR 2024 Conformal Prediction with Learned Features ICML 2024 Uncertainty quantification and robustification of model-based controllers using conformal prediction L4DC 2024 Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss ICML 2024 JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models NIPS 2024 Conformal Prediction Regions for Time Series Using Linear Complementarity Programming AAAI 2024 Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling AISTATS 2024 Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples ICML 2024 Active Collaborative Localization in Heterogeneous Robot Teams RSS 2023 The noise level in linear regression with dependent data NIPS 2023 Variational Autoencoding Neural Operators ICML 2023 Adaptive Conformal Prediction for Motion Planning among Dynamic Agents L4DC 2023 Certified Invertibility in Neural Networks via Mixed-Integer Programming L4DC 2023 Physics-enhanced Gaussian Process Variational Autoencoder L4DC 2023 Linear Stochastic Bandits over a Bit-Constrained Channel L4DC 2023 Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds NIPS 2022 NOMAD: Nonlinear Manifold Decoders for Operator Learning NIPS 2022 Learning Operators with Coupled Attention JMLR 2022 Adaptive Stochastic MPC under Unknown Noise Distribution L4DC 2022 Probabilistically Robust Learning: Balancing Average and Worst-case Performance ICML 2022 Do deep networks transfer invariances across classes? ICLR 2022 Learning to Control Linear Systems can be Hard COLT 2022 Probable Domain Generalization via Quantile Risk Minimization NIPS 2022 Adversarial Robustness with Semi-Infinite Constrained Learning NIPS 2021 Safe Pontryagin Differentiable Programming NIPS 2021 Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients NIPS 2021 Model-Based Domain Generalization NIPS 2021 Optimal Algorithms for Submodular Maximization with Distributed Constraints L4DC 2021 Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees L4DC 2020 Asymptotically Optimal Planning for Non-Myopic Multi-Robot Information Gathering RSS 2019 Assumed Density Filtering Q-learning IJCAI 2019 A Unifying View of Geometry, Semantics, and Data Association in SLAM IJCAI 2018