From the 1 of 9 linked papers with an AI index.
9 papers
Segregate, Refine, Integrate: Decomposing Multimodal Fusion for Sentiment Analysis
Alexios Filippakopoulos, Elias Kallioras, Nikolaos Xiros +2
The paper introduces SeRIn, a multimodal fusion architecture that separates modality-specific refinement from cross‑modal integration, improving sentiment analysis performance on b…
Auto-Compressing Networks
Vaggelis Dorovatas, Georgios Paraskevopoulos, Alexandros Potamianos
Deep neural networks with short residual connections have demonstrated remarkable success across domains, but increasing depth often introduces computational redundancy without cor…
Semantic F1 Scores: Fair Evaluation Under Fuzzy Class Boundaries
Georgios Chochlakis, Jackson Trager, Vedant Jhaveri +3
We propose Semantic F1 Scores, novel evaluation metrics for subjective or fuzzy multi-label classification that quantify semantic relatedness between predicted and gold labels. Unl…
Masked Diffusion Language Models with Frequency-Informed Training
Despoina Kosmopoulou, Efthymios Georgiou, Vaggelis Dorovatas +2
We present a masked diffusion language modeling framework for data-efficient training for the BabyLM 2025 Challenge. Our approach applies diffusion training objectives to language…
MEDUSA: A Multimodal Deep Fusion Multi-Stage Training Framework for Speech Emotion Recognition in Naturalistic Conditions
Georgios Chatzichristodoulou, Despoina Kosmopoulou, Antonios Kritikos +5
SER is a challenging task due to the subjective nature of human emotions and their uneven representation under naturalistic conditions. We propose MEDUSA, a multimodal framework wi…
BloomWise: Enhancing Problem-Solving capabilities of Large Language Models using Bloom's-Taxonomy-Inspired Prompts
Maria-Eleni Zoumpoulidi, Georgios Paraskevopoulos, Alexandros Potamianos
Despite the remarkable capabilities of large language models (LLMs) across a range of tasks, mathematical reasoning remains a challenging frontier. Motivated by the observation tha…