13 citations · 14 across the 4 of their papers we have counts for
6 papers
Understanding Evaluation Illusion in Diffusion Large Language Models
Hengxiang Zhang, Jiaxi Ren, Renchunzi Xie +1
Despite the capability of parallel decoding, diffusion large language models (dLLMs) require many denoising steps to maintain generation quality, motivating recent research on effi…
MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts
Renchunzi Xie, Ambroise Odonnat, Vasilii Feofanov +3
Leveraging the models' outputs, specifically the logits, is a common approach to estimating the test accuracy of a pre-trained neural network on out-of-distribution (OOD) samples w…
Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift
Renchunzi Xie, Ambroise Odonnat, Vasilii Feofanov +3
Estimating the test performance of a model, possibly under distribution shift, without having access to the ground-truth labels is a challenging, yet very important problem for the…
GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation
Renchunzi Xie, Hongxin Wei, Lei Feng +1
This paper studies weakly supervised domain adaptation(WSDA) problem, where we only have access to the source domain with noisy labels, from which we need to transfer useful inform…
Automatic Online Multi-Source Domain Adaptation
Renchunzi Xie, Mahardhika Pratama
Knowledge transfer across several streaming processes remain challenging problem not only because of different distributions of each stream but also because of rapidly changing and…
ATL: Autonomous Knowledge Transfer from Many Streaming Processes
Mahardhika Pratama, Marcus de Carvalho, Renchunzi Xie +2
Transferring knowledge across many streaming processes remains an uncharted territory in the existing literature and features unique characteristics: no labelled instance of the ta…