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cs.LG2026
Elastic Spectral State Space Models for Train-Once Budgeted Inference
Dachuan Song, Xuan Wang, Junyu Yin +1
Modern sequence models are typically trained at a fixed computational capacity, while real-world applications require deployment across platforms with different resource constraint…
cs.LG2025
BioArc: Discovering Optimal Neural Architectures for Biological Foundation Models
Yi Fang, Haoran Xu, Jiaxin Han +4
Foundation models have revolutionized various fields such as natural language processing (NLP) and computer vision (CV). While efforts have been made to transfer the success of the…