45 citations · 45 across the 3 of their papers we have counts for
3 papers
cs.CL2025
Order Matters: Rethinking Prompt Construction in In-Context Learning
Warren Li, Yiqian Wang, Zihan Wang +1
In-context learning (ICL) enables large language models to perform new tasks by conditioning on a sequence of examples. Most prior work reasonably and intuitively assumes that whic…
cs.LG2019★ 45 cited
Master your Metrics with Calibration
Wissam Siblini, Jordan Fréry, Liyun He-Guelton +2
Machine learning models deployed in real-world applications are often evaluated with precision-based metrics such as F1-score or AUC-PR (Area Under the Curve of Precision Recall).…
stat.ML2018
Adversarial confidence and smoothness regularizations for scalable unsupervised discriminative learning
Yi-Qing Wang
In this paper, we consider a generic probabilistic discriminative learner from the functional viewpoint and argue that, to make it learn well, it is necessary to constrain its hypo…