activity
20222024
most citedPorting Large Language Models to Mobile Devices for Question Answering

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20241 cited

Porting Large Language Models to Mobile Devices for Question Answering

Hannes Fassold

Deploying Large Language Models (LLMs) on mobile devices makes all the capabilities of natural language processing available on the device. An important use case of LLMs is questio…

cs.MM2023

A survey of manifold learning and its applications for multimedia

Hannes Fassold

Manifold learning is an emerging research domain of machine learning. In this work, we give an introduction into manifold learning and how it is employed for important application…

cs.LG2023

Do the Frankenstein, or how to achieve better out-of-distribution performance with manifold mixing model soup

Hannes Fassold

The standard recipe applied in transfer learning is to finetune a pretrained model on the task-specific dataset with different hyperparameter settings and pick the model with the h…

cs.CV2023

A real-time algorithm for human action recognition in RGB and thermal video

Hannes Fassold, Karlheinz Gutjahr, Anna Weber +1

Monitoring the movement and actions of humans in video in real-time is an important task. We present a deep learning based algorithm for human action recognition for both RGB and t…

cs.CV2022

FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level

Gabriele Lagani, Claudio Gennaro, Hannes Fassold +1

Learning algorithms for Deep Neural Networks are typically based on supervised end-to-end Stochastic Gradient Descent (SGD) training with error backpropagation (backprop). Backprop…