4 papers
LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models
Taekhyun Park, Yongjae Lee, Dohee Kim +1
Looped computation shows promise in improving the reasoning-oriented performance of LLMs by scaling test-time compute. However, existing approaches typically require either trainin…
ACFormer: Mitigating Non-linearity with Auto Convolutional Encoder for Time Series Forecasting
Gawon Lee, Hanbyeol Park, Minseop Kim +2
Time series forecasting (TSF) faces challenges in modeling complex intra-channel temporal dependencies and inter-channel correlations. Although recent research has highlighted the…
IConv: Focusing on Local Variation with Channel Independent Convolution for Multivariate Time Series Forecasting
Gawon Lee, Hanbyeol Park, Minseop Kim +2
Real-world time-series data often exhibit non-stationarity, including changing trends, irregular seasonality, and residuals. In terms of changing trends, recently proposed multi-la…
JustDense: Just using Dense instead of Sequence Mixer for Time Series analysis
TaekHyun Park, Yongjae Lee, Daesan Park +2
Sequence and channel mixers, the core mechanism in sequence models, have become the de facto standard in time series analysis (TSA). However, recent studies have questioned the nec…