4 citations · 11 across the 6 of their papers we have counts for
6 papers
Towards Effective and Efficient Continual Pre-training of Large Language Models
Jie Chen, Zhipeng Chen, Jiapeng Wang +16
Continual pre-training (CPT) has been an important approach for adapting language models to specific domains or tasks. To make the CPT approach more traceable, this paper presents…
Diagnosing and Re-learning for Balanced Multimodal Learning
Yake Wei, Siwei Li, Ruoxuan Feng +1
To overcome the imbalanced multimodal learning problem, where models prefer the training of specific modalities, existing methods propose to control the training of uni-modal encod…
SphereDiffusion: Spherical Geometry-Aware Distortion Resilient Diffusion Model
Tao Wu, Xuewei Li, Zhongang Qi +4
Controllable spherical panoramic image generation holds substantial applicative potential across a variety of domains.However, it remains a challenging task due to the inherent sph…
Quantifying and Enhancing Multi-modal Robustness with Modality Preference
Zequn Yang, Yake Wei, Ce Liang +1
Multi-modal models have shown a promising capability to effectively integrate information from various sources, yet meanwhile, they are found vulnerable to pervasive perturbations,…
Supervised Knowledge May Hurt Novel Class Discovery Performance
Ziyun Li, Jona Otholt, Ben Dai +3
Novel class discovery (NCD) aims to infer novel categories in an unlabeled dataset by leveraging prior knowledge of a labeled set comprising disjoint but related classes. Given tha…
Balanced Audiovisual Dataset for Imbalance Analysis
Wenke Xia, Xu Zhao, Xincheng Pang +2
The imbalance problem is widespread in the field of machine learning, which also exists in multimodal learning areas caused by the intrinsic discrepancy between modalities of sampl…