4 papers
K-EXAONE 2.0 Technical Report
Eunbi Choi, Kibong Choi, Sehyun Chun +74
This technical report presents K-EXAONE 2.0, an open-weight multilingual foundation model developed by LG AI Research as a step in our effort toward global frontier-scale foundatio…
Attention-space Contrastive Guidance for Efficient Hallucination Mitigation in LVLMs
Yujin Jo, Sangyoon Bae, Taesup Kim
Hallucinations in large vision--language models (LVLMs) often arise when language priors dominate over visual evidence, leading to object misidentification and visually inconsisten…
Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models
Yujin Jo, Taesup Kim
Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated remarkable zero-shot generalization, enabling deployment in a wide range of real-world tasks without addi…
Retaining and Enhancing Pre-trained Knowledge in Vision-Language Models with Prompt Ensembling
Donggeun Kim, Yujin Jo, Myungjoo Lee +1
The advancement of vision-language models, particularly the Contrastive Language-Image Pre-training (CLIP) model, has revolutionized the field of machine learning by enabling robus…