activity
20212026
most citedMMLatch: Bottom-up Top-down Fusion for Multimodal Sentiment Analysis

2 citations · 5 across the 15 of their papers we have counts for

collaborators
Showing cs.CLShow all

7 papers · 1 filter

cs.CL2026

The Illusion of Balanced Multimodal Sentiment Analysis: Beyond the Limits of Optimization-Based Methods

Ioanna Kaffeza, Efthymios Georgiou, Alexandros Potamianos

Multimodal Sentiment Analysis (MSA) remains constrained by modality imbalance, yet the field continues to rely on optimization-based balancing methods that promise more than they d…

cs.CL2026

Segregate, Refine, Integrate: Decomposing Multimodal Fusion for Sentiment Analysis

Alexios Filippakopoulos, Elias Kallioras, Nikolaos Xiros +2

Multimodal fusion must simultaneously refine modality-specific signals and model cross-modal interactions; two competing objectives typically entangled within the same operation. W…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

DeepMLF: Multimodal language model with learnable tokens for deep fusion in sentiment analysis

Efthymios Georgiou, Vassilis Katsouros, Yannis Avrithis +1

While multimodal fusion has been extensively studied in Multimodal Sentiment Analysis (MSA), the role of fusion depth and multimodal capacity allocation remains underexplored. In t…

cs.CL2023

PowMix: A Versatile Regularizer for Multimodal Sentiment Analysis

Efthymios Georgiou, Yannis Avrithis, Alexandros Potamianos

Multimodal sentiment analysis (MSA) leverages heterogeneous data sources to interpret the complex nature of human sentiments. Despite significant progress in multimodal architectur…