6 papers
A Closed-Form Solution for Debiasing Vision-Language Models with Utility Guarantees Across Modalities and Tasks
Tangzheng Lian, Guanyu Hu, Yijing Ren +2
While Vision-Language Models (VLMs) have achieved remarkable performance across diverse downstream tasks, recent studies have shown that they can inherit social biases from the tra…
FairMT: Fairness for Heterogeneous Multi-Task Learning
Guanyu Hu, Tangzheng Lian, Na Yan +5
Fairness in machine learning has been extensively studied in single-task settings, while fair multi-task learning (MTL), especially with heterogeneous tasks (classification, detect…
CausalAffect: Causal Discovery for Facial Affective Understanding
Guanyu Hu, Tangzheng Lian, Dimitrios Kollias +2
Understanding human affect from facial behavior requires not only accurate recognition but also structured reasoning over the latent dependencies that drive muscle activations and…
Grounding Emotion Recognition with Visual Prototypes: VEGA -- Revisiting CLIP in MERC
Guanyu Hu, Dimitrios Kollias, Xinyu Yang
Multimodal Emotion Recognition in Conversations remains a challenging task due to the complex interplay of textual, acoustic and visual signals. While recent models have improved p…
Rethinking Affect Analysis: A Protocol for Ensuring Fairness and Consistency
Guanyu Hu, Dimitrios Kollias, Eleni Papadopoulou +3
Evaluating affect analysis methods presents challenges due to inconsistencies in database partitioning and evaluation protocols, leading to unfair and biased results. Previous stud…
Robust Facial Reactions Generation: An Emotion-Aware Framework with Modality Compensation
Guanyu Hu, Jie Wei, Siyang Song +4
The objective of the Multiple Appropriate Facial Reaction Generation (MAFRG) task is to produce contextually appropriate and diverse listener facial behavioural responses based on…