5 papers
Elastic Selective Spectral Hybrids for Train-Once, Export-Many Budgeted Inference
Dachuan Song, Chuchu Chen, Xuan Wang
Deploying a language model under different computing and latency budgets calls for compact models with different quality-cost trade-offs. Towards this end, elastic spectral state s…
Mergeable Model-Side Aggregation States for Long-Context Language Models
Dachuan Song, Junyu Yin, Zechen Hu +1
A known limitation of long-context language models is their increasingly unreliable performance in non-additive, set-based aggregation as context length grows. Examples include car…
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…
Reconstructing Brain Causal Dynamics for Subject and Task Fingerprints using fMRI Time-series Data
Dachuan Song, Li Shen, Duy Duong-Tran +1
Purpose: Recently, there has been a revived interest in system neuroscience causation models, driven by their unique capability to unravel complex relationships in multi-scale brai…
Causality-based Subject and Task Fingerprints using fMRI Time-series Data
Dachuan Song, Li Shen, Duy Duong-Tran +1
Recently, there has been a revived interest in system neuroscience causation models due to their unique capability to unravel complex relationships in multi-scale brain networks. I…