68 citations · 137 across the 9 of their papers we have counts for
9 papers
A Study on the Calibration of In-context Learning
Hanlin Zhang, Yi-Fan Zhang, Yaodong Yu +5
Accurate uncertainty quantification is crucial for the safe deployment of machine learning models, and prior research has demonstrated improvements in the calibration of modern lan…
AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation
Yi-Fan Zhang, Xue Wang, Kexin Jin +5
Many recent machine learning tasks focus to develop models that can generalize to unseen distributions. Domain generalization (DG) has become one of the key topics in various field…
Evaluating Step-by-Step Reasoning through Symbolic Verification
Yi-Fan Zhang, Hanlin Zhang, Li Erran Li +1
Pre-trained language models (LMs) have shown remarkable reasoning performance using explanations or chain-of-thoughts (CoT)) for in-context learning. On the other hand, these reaso…
Domain-Specific Risk Minimization for Out-of-Distribution Generalization
Yi-Fan Zhang, Jindong Wang, Jian Liang +5
Recent domain generalization (DG) approaches typically use the hypothesis learned on source domains for inference on the unseen target domain. However, such a hypothesis can be arb…
Vision-Language Intelligence: Tasks, Representation Learning, and Large Models
Feng Li, Hao Zhang, Yi-Fan Zhang +5
This paper presents a comprehensive survey of vision-language (VL) intelligence from the perspective of time. This survey is inspired by the remarkable progress in both computer vi…
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation
Yi-Fan Zhang, Hanlin Zhang, Zachary C. Lipton +2
Previous works on Treatment Effect Estimation (TEE) are not in widespread use because they are predominantly theoretical, where strong parametric assumptions are made but untractab…
Towards Principled Disentanglement for Domain Generalization
Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu +3
A fundamental challenge for machine learning models is generalizing to out-of-distribution (OOD) data, in part due to spurious correlations. To tackle this challenge, we first form…
Learning Domain Invariant Representations for Generalizable Person Re-Identification
Yi-Fan Zhang, Zhang Zhang, Da Li +3
Generalizable person Re-Identification (ReID) has attracted growing attention in recent computer vision community. In this work, we construct a structural causal model among identi…
Focal and Efficient IOU Loss for Accurate Bounding Box Regression
Yi-Fan Zhang, Weiqiang Ren, Zhang Zhang +3
In object detection, bounding box regression (BBR) is a crucial step that determines the object localization performance. However, we find that most previous loss functions for BBR…