5 papers
Neural-Driven Image Editing
Pengfei Zhou, Jie Xia, Xiaopeng Peng +15
Traditional image editing typically relies on manual prompting, making it labor-intensive and inaccessible to individuals with limited motor control or language abilities. Leveragi…
On Weak-to-Strong Generalization and f-Divergence
Wei Yao, Gengze Xu, Huayi Tang +4
Weak-to-strong generalization (W2SG) has emerged as a promising paradigm for stimulating the capabilities of strong pre-trained models by leveraging supervision from weaker supervi…
DD-Ranking: Rethinking the Evaluation of Dataset Distillation
Zekai Li, Xinhao Zhong, Samir Khaki +49
In recent years, dataset distillation has provided a reliable solution for data compression, where models trained on the resulting smaller synthetic datasets achieve performance co…
Ensemble Debiasing Across Class and Sample Levels for Fairer Prompting Accuracy
Ruixi Lin, Ziqiao Wang, Yang You
Language models are strong few-shot learners and achieve good overall accuracy in text classification tasks, masking the fact that their results suffer from great class accuracy im…
MutualVPR: A Mutual Learning Framework for Resolving Supervision Inconsistencies via Adaptive Clustering
Qiwen Gu, Xufei Wang, Junqiao Zhao +4
Visual Place Recognition (VPR) enables robust localization through image retrieval based on learned descriptors. However, drastic appearance variations of images at the same place…