From the 1 of 10 linked papers with an AI index.
7 papers · 1 filter
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…
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…
MSDA: Combining Pseudo-labeling and Self-Supervision for Unsupervised Domain Adaptation in ASR
Dimitrios Damianos, Georgios Paraskevopoulos, Alexandros Potamianos
In this work, we investigate the Meta PL unsupervised domain adaptation framework for Automatic Speech Recognition (ASR). We introduce a Multi-Stage Domain Adaptation pipeline (MSD…
Aggregation Artifacts in Subjective Tasks Collapse Large Language Models' Posteriors
Georgios Chochlakis, Alexandros Potamianos, Kristina Lerman +1
In-context Learning (ICL) has become the primary method for performing natural language tasks with Large Language Models (LLMs). The knowledge acquired during pre-training is cruci…