Jiaya Jia

Exploring Self-Attention for Image Recognition

2020

Recent work has shown that self-attention can serve as a basic building block for image recognition models. We explore variations of self-attention and assess their effectiveness for image recognition. We consider two forms of self-attention. …

Improving Calibration for Long-Tailed Recognition

2021 · arXiv (Cornell University)

Deep neural networks may perform poorly when training datasets are heavily class-imbalanced. Recently, two-stage methods decouple representation learning and classifier learning to improve performance. But there is still the vital issue of miscalibration. To address …

BAL: Balancing Diversity and Novelty for Active Learning

2023 · arXiv (Cornell University)

The objective of Active Learning is to strategically label a subset of the dataset to maximize performance within a predetermined labeling budget. In this study, we harness features acquired through self-supervised learning. We introduce a …

Logits-Based Finetuning

2025

In recent years, developing compact and efficient large language models (LLMs) has emerged as a thriving area of research.Traditional Supervised Fine-Tuning (SFT), which relies on singular ground truth labels, often fails to capture token-level dependencies …