1 citations · 2 across the 9 of their papers we have counts for
10 papers
CycleCap: Improving VLMs Captioning Performance via Self-Supervised Cycle Consistency Fine-Tuning
Marios Krestenitis, Christos Tzelepis, Konstantinos Ioannidis +5
Visual-Language Models (VLMs) have achieved remarkable progress in image captioning, visual question answering, and visual reasoning. Yet they remain prone to vision-language misal…
Deconstructing the Failure of Ideal Noise Correction: A Three-Pillar Diagnosis
Chen Feng, Zhuo Zhi, Zhao Huang +5
Statistically consistent methods based on the noise transition matrix () offer a theoretically grounded solution to Learning with Noisy Labels (LNL), with guarantees of converge…
Relax Forcing: Relaxed KV-Memory for Consistent Long Video Generation
Zengqun Zhao, Yanzuo Lu, Ziquan Liu +3
Autoregressive video diffusion has recently emerged as a promising paradigm for long-video generation, enabling causal synthesis beyond the temporal limits of bidirectional models.…
LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion
Zengqun Zhao, Ziquan Liu, Yu Cao +5
The recent success of inference-time scaling in large language models has inspired similar explorations in video diffusion. In particular, motivated by the existence of "golden noi…
Breaking Language Barriers or Reinforcing Bias? A Study of Gender and Racial Disparities in Multilingual Contrastive Vision Language Models
Zahraa Al Sahili, Ioannis Patras, Matthew Purver
Multilingual vision-language models (VLMs) promise universal image-text retrieval, yet their social biases remain underexplored. We perform the first systematic audit of four publi…
Data Matters Most: Auditing Social Bias in Contrastive Vision Language Models
Zahraa Al Sahili, Ioannis Patras, Matthew Purver
Vision-language models (VLMs) deliver strong zero-shot recognition but frequently inherit social biases from their training data. We systematically disentangle three design factors…
Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization
Zhaohan Zhang, Ziquan Liu, Ioannis Patras
Large Language Models (LLMs) have been found to memorize and recite some of the textual sequences from their training set verbatim, raising broad concerns about privacy and copyrig…
Multimodal Machine Learning in Mental Health: A Survey of Data, Algorithms, and Challenges
Zahraa Al Sahili, Ioannis Patras, Matthew Purver
Multimodal machine learning (MML) is rapidly reshaping the way mental-health disorders are detected, characterized, and longitudinally monitored. Whereas early studies relied on is…
FairCoT: Enhancing Fairness in Text-to-Image Generation via Chain of Thought Reasoning with Multimodal Large Language Models
Zahraa Al Sahili, Ioannis Patras, Matthew Purver
In the domain of text-to-image generative models, biases inherent in training datasets often propagate into generated content, posing significant ethical challenges, particularly i…
FashionSD-X: Multimodal Fashion Garment Synthesis using Latent Diffusion
Abhishek Kumar Singh, Ioannis Patras
The rapid evolution of the fashion industry increasingly intersects with technological advancements, particularly through the integration of generative AI. This study introduces a…