2 citations · 3 across the 7 of their papers we have counts for
7 papers
S-JEPA : Soft Clustering Anchors for Self-Supervised Speech Representation Learning
Georgios Ioannides, Adrian Kieback, Judah Goldfeder +5
Self-supervised speech encoders are predominantly trained by predicting discrete hard cluster IDs at masked positions, a recipe that collapses acoustic ambiguity at category bounda…
Soft Clustering Anchors for Self-Supervised Speech Representation Learning in Joint Embedding Prediction Architectures
Georgios Ioannides, Adrian Kieback, Judah Goldfeder +5
Joint Embedding Predictive Architectures (JEPA) offer a promising approach to self-supervised speech representation learning, but suffer from representation collapse without explic…
JEPA as a Neural Tokenizer: Learning Robust Speech Representations with Density Adaptive Attention
Georgios Ioannides, Christos Constantinou, Aman Chadha +4
We introduce a two-stage self-supervised framework that combines the Joint-Embedding Predictive Architecture (JEPA) with a Density Adaptive Attention Mechanism (DAAM) for learning…
MOD-X: A Modular Open Decentralized eXchange Framework proposal for Heterogeneous Interoperable Artificial Intelligence Agents
Georgios Ioannides, Christos Constantinou, Vinija Jain +2
As Artificial Intelligence systems evolve from monolithic models to ecosystems of specialized agents, the need for standardized communication protocols becomes increasingly critica…
Density Adaptive Attention-based Speech Network: Enhancing Feature Understanding for Mental Health Disorders
Georgios Ioannides, Adrian Kieback, Aman Chadha +1
Speech-based depression detection poses significant challenges for automated detection due to its unique manifestation across individuals and data scarcity. Addressing these challe…
Out-of-Distribution Detection with Attention Head Masking for Multimodal Document Classification
Christos Constantinou, Georgios Ioannides, Aman Chadha +2
Detecting out-of-distribution (OOD) data is crucial in machine learning applications to mitigate the risk of model overconfidence, thereby enhancing the reliability and safety of d…
Density Adaptive Attention is All You Need: Robust Parameter-Efficient Fine-Tuning Across Multiple Modalities
Georgios Ioannides, Aman Chadha, Aaron Elkins
We propose the Multi-Head Density Adaptive Attention Mechanism (DAAM), a novel probabilistic attention framework that can be used for Parameter-Efficient Fine-tuning (PEFT), and th…