17 citations · 22 across the 7 of their papers we have counts for
7 papers
Omni-R1: Do You Really Need Audio to Fine-Tune Your Audio LLM?
Andrew Rouditchenko, Saurabhchand Bhati, Edson Araujo +4
We propose Omni-R1 which fine-tunes a recent multi-modal LLM, Qwen2.5-Omni, on an audio question answering dataset with the reinforcement learning method GRPO. This leads to new St…
Convolutional Differentiable Logic Gate Networks
Felix Petersen, Hilde Kuehne, Christian Borgelt +2
With the increasing inference cost of machine learning models, there is a growing interest in models with fast and efficient inference. Recently, an approach for learning logic gat…
Contrastive Audio-Visual Masked Autoencoder
Yuan Gong, Andrew Rouditchenko, Alexander H. Liu +4
In this paper, we first extend the recent Masked Auto-Encoder (MAE) model from a single modality to audio-visual multi-modalities. Subsequently, we propose the Contrastive Audio-Vi…
Augmentation Learning for Semi-Supervised Classification
Tim Frommknecht, Pedro Alves Zipf, Quanfu Fan +2
Recently, a number of new Semi-Supervised Learning methods have emerged. As the accuracy for ImageNet and similar datasets increased over time, the performance on tasks beyond the…
Routing with Self-Attention for Multimodal Capsule Networks
Kevin Duarte, Brian Chen, Nina Shvetsova +7
The task of multimodal learning has seen a growing interest recently as it allows for training neural architectures based on different modalities such as vision, text, and audio. O…
AVLnet: Learning Audio-Visual Language Representations from Instructional Videos
Andrew Rouditchenko, Angie Boggust, David Harwath +11
Current methods for learning visually grounded language from videos often rely on text annotation, such as human generated captions or machine generated automatic speech recognitio…
Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences
Rosaura G. VidalMata, Walter J. Scheirer, Anna Kukleva +2
Understanding the structure of complex activities in untrimmed videos is a challenging task in the area of action recognition. One problem here is that this task usually requires a…