Time-series foundation models (TSFMs) perform strongly across forecasting tasks, but their per-series inference is ill-suited to neighbor-rich forecasting, where each query has access to related but nonidentical historical series. Continuous glucose monitoring (CGM) and Web/cloud workloads exemplify this setting: CGM t...
Hao-Nan Shi, Tong Wu, Chen-Cong Sun et al.· 0 citations
This work introduces RouteFM, which learns to characterize anonymous candidate models from behavioral context and infer their target-specific capabilities, rather than binding routing decisions to fixed model identities or a single environment, and shows transfer across changes in domains, modalities, candidate pools,...
This paper systematically identifies one of the fundamental challenges behind CIL, named feature collision, where the features learned by the current task-specific model may collide with those of the previous models, leading to forgetting of previously learned tasks and hindering the learning of new tasks.
Bowen Zheng, Zijun Shen, Da-Wei Zhou et al.· International Journal of Com...· 0 citations
ResiSpec, a framework that strategically reforms the proposal distribution during verification to anchor the residual target mass within the draft model's high-confidence regions, prevents candidate obsolescence and achieves up to 1.92$\times$ speedup over state-of-the-art multi-candidate methods.
Zhi-Kai Chen, Jun Tao, Wei-Hao Mao et al.· 1 citation
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