3 citations · 5 across the 7 of their papers we have counts for
4 papers · 1 filter
A Unified Framework for Connecting Noise Modeling to Boost Noise Detection
Siqi Wang, Chau Pham, Bryan A. Plummer
Noisy labels can impair model performance, making the study of learning with noisy labels an important topic. Two conventional approaches are noise modeling and noise detection. Ho…
MixtureGrowth: Growing Neural Networks by Recombining Learned Parameters
Chau Pham, Piotr Teterwak, Soren Nelson +1
Most deep neural networks are trained under fixed network architectures and require retraining when the architecture changes. If expanding the network's size is needed, it is neces…
CHAMMI: A benchmark for channel-adaptive models in microscopy imaging
Zitong Chen, Chau Pham, Siqi Wang +4
Most neural networks assume that input images have a fixed number of channels (three for RGB images). However, there are many settings where the number of channels may vary, such a…
Let Models Speak Ciphers: Multiagent Debate through Embeddings
Chau Pham, Boyi Liu, Yingxiang Yang +6
Discussion and debate among Large Language Models (LLMs) have gained considerable attention due to their potential to enhance the reasoning ability of LLMs. Although natural langua…