activity
20182025
most citedAugLy: Data Augmentations for Robustness

27 citations · 29 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CL2025

ZeroSumEval: An Extensible Framework For Scaling LLM Evaluation with Inter-Model Competition

Hisham A. Alyahya, Haidar Khan, Yazeed Alnumay +2

We introduce ZeroSumEval, a dynamic, competition-based, and evolving evaluation framework for Large Language Models (LLMs) that leverages competitive games. ZeroSumEval encompasses…

cs.CL2025★ 1 cited

Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study

Menglong Cui, Pengzhi Gao, Wei Liu +2

Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…

cs.CL2024

LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch

Jan Pfister, Julia Wunderle, Andreas Hotho

We create two German-only decoder models, LLäMmlein 120M and 1B, transparently from scratch and publish them, along with the training data, for the German NLP research community to…

cs.AI2024

The Llama 3 Herd of Models

Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models th…

cs.CV2023

Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis

Maxim Maximov, Tim Meinhardt, Ismail Elezi +4

The advent of data-driven technology solutions is accompanied by an increasing concern with data privacy. This is of particular importance for human-centered image recognition task…

cs.CV2022★ 1 cited

Results and findings of the 2021 Image Similarity Challenge

Zoë Papakipos, Giorgos Tolias, Tomas Jenicek +11

The 2021 Image Similarity Challenge introduced a dataset to serve as a new benchmark to evaluate recent image copy detection methods. There were 200 participants to the competition…

cs.AI2022★ 27 cited

AugLy: Data Augmentations for Robustness

Zoe Papakipos, Joanna Bitton

We introduce AugLy, a data augmentation library with a focus on adversarial robustness. AugLy provides a wide array of augmentations for multiple modalities (audio, image, text, &…

cs.HC2019

Stackelberg Punishment and Bully-Proofing Autonomous Vehicles

Matt Cooper, Jun Ki Lee, Jacob Beck +7

Mutually beneficial behavior in repeated games can be enforced via the threat of punishment, as enshrined in game theory's well-known "folk theorem." There is a cost, however, to a…

cs.LG2019

ReNeg and Backseat Driver: Learning from Demonstration with Continuous Human Feedback

Jacob Beck, Zoe Papakipos, Michael Littman

In autonomous vehicle (AV) control, allowing mistakes can be quite dangerous and costly in the real world. For this reason we investigate methods of training an AV without allowing…

cs.LG2018

Neural Mesh: Introducing a Notion of Space and Conservation of Energy to Neural Networks

Jacob Beck, Zoe Papakipos

Neural networks are based on a simplified model of the brain. In this project, we wanted to relax the simplifying assumptions of a traditional neural network by making a model that…