output
20212025
most citedLearning to Break Deep Perceptual Hashing: The Use Case NeuralHash

140 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

9 papers

cs.LG2025

Prompting Neural-Guided Equation Discovery Based on Residuals

Jannis Brugger, Viktor Pfanschilling, David Richter +2

Neural-guided equation discovery systems use a data set as prompt and predict an equation that describes the data set without extensive search. However, if the equation does not me…

cs.RO2024

Learning to Play Foosball: System and Baselines

Janosch Moos, Cedric Derstroff, Niklas Schröder +1

This work stages Foosball as a versatile platform for advancing scientific research, particularly in the realm of robot learning. We present an automated Foosball table along with…

cs.RO2024★ 11 cited

MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions from Demonstrations

Vignesh Prasad, Alap Kshirsagar, Dorothea Koert +3

Shared dynamics models are important for capturing the complexity and variability inherent in Human-Robot Interaction (HRI). Therefore, learning such shared dynamics models can enh…

cs.SE2024★ 4 cited

Towards Trustworthy AI Software Development Assistance

Daniel Maninger, Krishna Narasimhan, Mira Mezini

It is expected that in the near future, AI software development assistants will play an important role in the software industry. However, current software development assistants te…

cs.CV2024★ 2 cited

Caregiver Talk Shapes Toddler Vision: A Computational Study of Dyadic Play

Timothy Schaumlöffel, Arthur Aubret, Gemma Roig +1

Infants' ability to recognize and categorize objects develops gradually. The second year of life is marked by both the emergence of more semantic visual representations and a bette…

cs.LG2023★ 2 cited

Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations

Cedric Derstroff, Mattia Cerrato, Jannis Brugger +2

Peer learning is a novel high-level reinforcement learning framework for agents learning in groups. While standard reinforcement learning trains an individual agent in trial-and-er…

cs.PL2023★ 5 cited

LoRe: A Programming Model for Verifiably Safe Local-First Software

Julian Haas, Ragnar Mogk, Elena Yanakieva +2

Local-first software manages and processes private data locally while still enabling collaboration between multiple parties connected via partially unreliable networks. Such softwa…

cs.CL2022★ 11 cited

A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing

Allison Lahnala, Charles Welch, David Jurgens +1

We review the state of research on empathy in natural language processing and identify the following issues: (1) empathy definitions are absent or abstract, which (2) leads to low…

cs.LG2021★ 140 cited

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash

Lukas Struppek, Dominik Hintersdorf, Daniel Neider +1

Apple recently revealed its deep perceptual hashing system NeuralHash to detect child sexual abuse material (CSAM) on user devices before files are uploaded to its iCloud service.…