1 citations · 1 across the 5 of their papers we have counts for
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TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models
Hongkai Li, Shifeng Xie, Lefei Shen +7
Time series foundation models (TSFMs) are increasingly pretrained on large corpora, raising concerns that evaluation datasets may have been exposed during pretraining and thus yiel…
Multi-Scale Finetuning for Encoder-based Time Series Foundation Models
Zhongzheng Qiao, Chenghao Liu, Yiming Zhang +6
Time series foundation models (TSFMs) demonstrate impressive zero-shot performance for time series forecasting. However, an important yet underexplored challenge is how to effectiv…
CompeteSMoE -- Effective Training of Sparse Mixture of Experts via Competition
Quang Pham, Giang Do, Huy Nguyen +8
Sparse mixture of experts (SMoE) offers an appealing solution to scale up the model complexity beyond the mean of increasing the network's depth or width. However, effective traini…
HyperRouter: Towards Efficient Training and Inference of Sparse Mixture of Experts
Giang Do, Khiem Le, Quang Pham +7
By routing input tokens to only a few split experts, Sparse Mixture-of-Experts has enabled efficient training of large language models. Recent findings suggest that fixing the rout…