Nathalie Rauschmayr

16 papers A* 5Misc 2Journal 6Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	I Know What I Don't Know: Improving Model Cascades Through Confidence Tuning. CoRR Stephan Rabanser, Nathalie Rauschmayr, Achin Kulshrestha, Petra Poklukar, Wittawat Jitkrittum, Sean Augenstein, Congchao Wang, Federico Tombari
2025	A*	`conf`	Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence. ICML Shangbin Feng, Zifeng Wang, Yike Wang, Sayna Ebrahimi, Hamid Palangi, Lesly Miculicich, Achin Kulshrestha, Nathalie Rauschmayr, Yejin Choi, Yulia Tsvetkov, Chen-Yu Lee, Tomas Pfister
2025	J	`jnl`	Reading Between the Lines: Abstaining from VLM-Generated OCR Errors via Latent Representation Probes. CoRR Jihan Yao, Achin Kulshrestha, Nathalie Rauschmayr, Reed Roberts, Banghua Zhu, Yulia Tsvetkov, Federico Tombari
2025	A*	`conf`	Test-Time Visual In-Context Tuning. CVPR Jiahao Xie, Alessio Tonioni, Nathalie Rauschmayr, Federico Tombari, Bernt Schiele
2025	J	`jnl`	Test-Time Visual In-Context Tuning. CoRR Jiahao Xie, Alessio Tonioni, Nathalie Rauschmayr, Federico Tombari, Bernt Schiele
2024	A*	`conf`	Extracting Training Data From Document-Based VQA Models. ICML Francesco Pinto, Nathalie Rauschmayr, Florian Tramèr, Philip Torr, Federico Tombari
2024	J	`jnl`	Extracting Training Data from Document-Based VQA Models. CoRR Francesco Pinto, Nathalie Rauschmayr, Florian Tramèr, Philip Torr, Federico Tombari
2024	J	`jnl`	Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence. CoRR Shangbin Feng, Zifeng Wang, Yike Wang, Sayna Ebrahimi, Hamid Palangi, Lesly Miculicich, Achin Kulshrestha, Nathalie Rauschmayr, Yejin Choi, Yulia Tsvetkov, Chen-Yu Lee, Tomas Pfister
2022	A*	`conf`	Generating Distributional Adversarial Examples to Evade Statistical Detectors. ICML Yigitcan Kaya, Muhammad Bilal Zafar, Sergül Aydöre, Nathalie Rauschmayr, Krishnaram Kenthapadi
2022	A*	`conf`	Profiling Deep Learning Workloads at Scale using Amazon SageMaker. KDD Nathalie Rauschmayr, Sami Kama, Muhyun Kim, Miyoung Choi, Krishnaram Kenthapadi
2021	—	`conf`	Amazon SageMaker Debugger: A System for Real-Time Insights into Machine Learning Model Training. MLSys Nathalie Rauschmayr, Vikas Kumar, Rahul Huilgol, Andrea Olgiati, Satadal Bhattacharjee, Nihal Harish, Vandana Kannan, Amol Lele, Anirudh Acharya, Jared Nielsen, Lakshmi Ramakrishnan, Ishan Bhatt, Kohen Chia, Neelesh Dodda, Zhihan Li, Jiacheng Gu, Miyoung Choi, Balajee Nagarajan, Jeffrey Geevarghese, Denis Davydenko, Sifei Li, Lu Huang, Edward Kim, Tyler Hill, Krishnaram Kenthapadi
2021	J	`jnl`	Defuse: Harnessing Unrestricted Adversarial Examples for Debugging Models Beyond Test Accuracy. CoRR Dylan Slack, Nathalie Rauschmayr, Krishnaram Kenthapadi
2014	—	`—`	Optimisation of LHCb Applications for Multi- and Manycore Job Submission. Nathalie Rauschmayr
2013	Misc	`conf`	Evaluating Moldability of LHCb Jobs for Multicore Job Submission. SYNASC Nathalie Rauschmayr, Achim Streit
2013	Misc	`conf`	Evaluation of x32-ABI in the Context of LHC Applications. ICCS Nathalie Rauschmayr, Achim Streit
2012	—	`conf`	Reducing the Memory Footprint of Parallel Applications with KSM. Facing the Multicore-Challenge Nathalie Rauschmayr, Achim Streit