4 citations · 4 across the 11 of their papers we have counts for
5 papers · 1 filter
NTKMTL: Mitigating Task Imbalance in Multi-Task Learning from Neural Tangent Kernel Perspective
Xiaohan Qin, Xiaoxing Wang, Ning Liao +1
Multi-Task Learning (MTL) enables a single model to learn multiple tasks simultaneously, leveraging knowledge transfer among tasks for enhanced generalization, and has been widely…
Innovator: Scientific Continued Pretraining with Fine-grained MoE Upcycling
Ning Liao, Xiaoxing Wang, Zehao Lin +18
A large language model (LLM) with knowledge in both scientific and general tasks is the foundation of science general intelligence. However, directly continued pretraining an LLM u…
Modeling All Response Surfaces in One for Conditional Search Spaces
Jiaxing Li, Wei Liu, Chao Xue +4
Bayesian Optimization (BO) is a sample-efficient black-box optimizer commonly used in search spaces where hyperparameters are independent. However, in many practical AutoML scenari…
Poisson Process for Bayesian Optimization
Xiaoxing Wang, Jiaxing Li, Chao Xue +5
BayesianOptimization(BO) is a sample-efficient black-box optimizer, and extensive methods have been proposed to build the absolute function response of the black-box function throu…
DARTS-: Robustly Stepping out of Performance Collapse Without Indicators
Xiangxiang Chu, Xiaoxing Wang, Bo Zhang +3
Despite the fast development of differentiable architecture search (DARTS), it suffers from long-standing performance instability, which extremely limits its application. Existing…