Maximilian Baader
14 papers · 2019–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π Cross-Pollinator (11) π Conference Polyglot (5) π§ Keyword Pioneer π Academic Marathon (6) π Renaissance Researcher (5)
π
Interdisciplinary Bridge
πΊοΈ
Taxonomy Completionist
(21)
π§
Keyword Pioneer
π
Grand Slam
π€
Dynamic Duo
(14)
β
The Questioner
β‘
Prolific Year
(5)
π
Trend Setter
π
Century Club
(14)
Conferences
ICLR (5)
NIPS (4)
ICML (3)
AAAI (1)
ECCV (1)
Top co-authors
Research topics
Keywords
privacy attack
(2)
adversarial robustness
(2)
randomized smoothing
(2)
gradient inversion
(2)
exact reconstruction
(2)
computer vision
(2)
federated learning
(2)
point cloud
(1)
formal verification
(1)
convex relaxation
(1)
adversarial attack
(1)
adversarial defense
(1)
robustness certification
(1)
neural network verification
(1)
neural network robustness
(1)
token recovery
(1)
geometric transformation
(1)
image transformation
(1)
gradient inversion attack
(1)
exhaustive search
(1)
Papers
Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation
ICLR 2025
GRAIN: Exact Graph Reconstruction from Gradients
ICLR 2025
Ward: Provable RAG Dataset Inference via LLM Watermarks
ICLR 2025
BaxBench: Can LLMs Generate Correct and Secure Backends?
ICML 2025
A Unified Approach to Routing and Cascading for LLMs
ICML 2025
Expressivity of ReLU-Networks under Convex Relaxations
ICLR 2024
DAGER: Exact Gradient Inversion for Large Language Models
NIPS 2024
SPEAR: Exact Gradient Inversion of Batches in Federated Learning
NIPS 2024
Latent Space Smoothing for Individually Fair Representations
ECCV 2022
Scalable Certified Segmentation via Randomized Smoothing
ICML 2021
Efficient Certification of Spatial Robustness
AAAI 2021
Universal Approximation with Certified Networks
ICLR 2020
Certified Defense to Image Transformations via Randomized Smoothing
NIPS 2020
Certifying Geometric Robustness of Neural Networks
NIPS 2019