5 papers
Expert-guided Clinical Text Augmentation via Query-Based Model Collaboration
Dongkyu Cho, Miao Zhang, Rumi Chunara
Data augmentation is a widely used strategy to improve model robustness and generalization by enriching training datasets with synthetic examples. While large language models (LLMs…
Label Shift Aware Adaptation for Online Zero-shot Learning with Contrastive Language-Image Pre-Training (CLIP)
Pengxiao Han, Changkun Ye, Yanshuo Wang +5
Vision-language models like Contrastive Language-Image Pre-Training (CLIP) have been extensively studied in data-scarce scenarios. A particularly challenging and realistic task in…
Identity-Robust Language Model Generation via Content Integrity Preservation
Miao Zhang, Kelly Chen, Md Mehrab Tanjim +1
Large Language Model (LLM) outputs often vary across user sociodemographic attributes, leading to disparities in factual accuracy, utility, and safety, even for objective questions…
Configurable Fairness: Direct Optimization of Parity Metrics via Vision-Language Models
Miao Zhang, Rumi Chunara
Performance disparities of image recognition across demographic groups are known to exist in deep learning-based models, due to imbalanced group representations or spurious correla…
Enhancing Diffusion-based Dataset Distillation via Adversary-Guided Curriculum Sampling
Lexiao Zou, Gongwei Chen, Yanda Chen +1
Dataset distillation aims to encapsulate the rich information contained in dataset into a compact distilled dataset but it faces performance degradation as the image-per-class (IPC…