Researcher — paper.dinq.me

2026 顶会论文

作者位次 #6/6ICML 2026Poster· Social Aspects / Robustness

Position: LLM-Safety Evaluations Lack Robustness

Tim Beyer · Sophie Xhonneux · Simon Geisler · Gauthier Gidel · Leo Schwinn · Stephan Günnemann

安全评测与基准社会与人本OpenReview

作者位次 #4/6ICML 2026Poster· Applications / Health / Medicine

Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics

Egor Antipov · Alessandro Palma · Lorenzo Consoli · Stephan Günnemann · Andrea Dittadi · Fabian Theis

社会与人本OpenReview

作者位次 #4/4ICML 2026Spotlight· Applications / Chemistry, Physics, and Earth Sciences

Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State

Nicholas Gao · Till Grutschus · Frank Noe · Stephan Günnemann

理论与学习动力学OpenReview

作者位次 #3/3ICML 2026Poster· Deep Learning / Large Language Models

Task-Awareness Improves LLM Generations and Uncertainty

Tim Tomov · Dominik Fuchsgruber · Stephan Günnemann

OpenReview

作者位次 #2/4ICML 2026Poster· Applications / Chemistry, Physics, and Earth Sciences

Speculative Sampling For Faster Molecular Dynamics

Arthur Kosmala · Stephan Günnemann · Meng Gao · Brandon Wood

效率与系统OpenReview

作者位次 #8/8ICML 2026Poster· Applications / Chemistry, Physics, and Earth Sciences

Derivative Informed Learning of Exchange-Correlation Functionals

Eike S. Eberhard · Luca Anthony Thiede · Abdulrahman Aldossary · Andreas Burger · Nicholas Gao · Vignesh Bhethanabotla · Alan Aspuru-Guzik · Stephan Günnemann

OpenReview

作者位次 #6/6ICML 2026Poster· Deep Learning / Robustness

A Coin Flip for Safety: LLM Judges Fail to Reliably Measure Adversarial Robustness

Leo Schwinn · Moritz Ladenburger · Tim Beyer · Mehrnaz Mofakhami · Gauthier Gidel · Stephan Günnemann

安全评测与基准OpenReview

作者位次 #3/4ICML 2026Poster· Deep Learning / Sequential Models, Time series

Byte Pair Encoding for Efficient Time Series Forecasting

Leon Götz · Marcel Kollovieh · Stephan Günnemann · Leo Schwinn

效率与系统代码OpenReview

作者位次 #4/4ICML 2026Poster· Deep Learning / Graph Neural Networks

Certifying Graph Neural Networks Against Label and Structure Poisoning

Lukas Gosch · Xichuan Chen · Yan Scholten · Stephan Günnemann

OpenReview

Stephan Günnemann

获取完整研究档案

联系方式

2026 顶会论文

Position: LLM-Safety Evaluations Lack Robustness

Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics

Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State

Task-Awareness Improves LLM Generations and Uncertainty

Speculative Sampling For Faster Molecular Dynamics

Derivative Informed Learning of Exchange-Correlation Functionals

A Coin Flip for Safety: LLM Judges Fail to Reliably Measure Adversarial Robustness

Byte Pair Encoding for Efficient Time Series Forecasting

Certifying Graph Neural Networks Against Label and Structure Poisoning

常见合作者