1 citations · 1 across the 4 of their papers we have counts for
5 papers
PANICL: Mitigating Over-Reliance on Single Prompt in Visual In-Context Learning
Jiahao Zhang, Bowen Wang, Hong Liu +2
Visual In-Context Learning (VICL) uses input-output image pairs, referred to as in-context pairs (or examples), as prompts alongside query images to guide models in performing dive…
E-InMeMo: Enhanced Prompting for Visual In-Context Learning
Jiahao Zhang, Bowen Wang, Hong Liu +3
Large-scale models trained on extensive datasets have become the standard due to their strong generalizability across diverse tasks. In-context learning (ICL), widely used in natur…
MIDAS: Mixing Ambiguous Data with Soft Labels for Dynamic Facial Expression Recognition
Ryosuke Kawamura, Hideaki Hayashi, Noriko Takemura +1
Dynamic facial expression recognition (DFER) is an important task in the field of computer vision. To apply automatic DFER in practice, it is necessary to accurately recognize ambi…
DiReCT: Diagnostic Reasoning for Clinical Notes via Large Language Models
Bowen Wang, Jiuyang Chang, Yiming Qian +6
Large language models (LLMs) have recently showcased remarkable capabilities, spanning a wide range of tasks and applications, including those in the medical domain. Models like GP…
Explainable Image Recognition via Enhanced Slot-attention Based Classifier
Bowen Wang, Liangzhi Li, Jiahao Zhang +2
The imperative to comprehend the behaviors of deep learning models is of utmost importance. In this realm, Explainable Artificial Intelligence (XAI) has emerged as a promising aven…