Search Results for author:
Found 4 papers, 4 papers with code
Leveraging Normalization Layer in Adapters With Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning
Second, to address the pitfalls of noisy statistics, we deploy two strategies: a progressive training of the two adapters and an adaptive distillation technique derived from features determined by the model solely with the adapter devoid of a normalization layer.
Improving Adaptability and Generalizability of Efficient Transfer Learning for Vision-Language Models
Vision-Language Models (VLMs) like CLIP have demonstrated remarkable applicability across a variety of downstream tasks, including zero-shot image classification.
HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning
With the proliferation of social media, accurate detection of hate speech has become critical to ensure safety online.
Meta-Learning with Adaptive Weighted Loss for Imbalanced Cold-Start Recommendation
To alleviate this limitation, we propose a novel sequential recommendation framework based on gradient-based meta-learning that captures the imbalanced rating distribution of each user and computes adaptive loss for user-specific learning.
