1 citations · 1 across the 9 of their papers we have counts for
4 papers · 2 filters
Explaining Time Series Forecasting with Horizon-Resolved Attribution
Seunghan Lee, Jun Seo, Jaehoon Lee +9
Recent advances in explaining time series (TS) models have produced methods that identify which past values a prediction depends on. However, most existing methods return a single…
FinVerse: Financial Time-Series Benchmark
Jaehoon Lee, Jun Seo, Seunghan Lee +9
As time-series foundation models have emerged, the need for benchmarks that can evaluate their forecasting ability in meaningful ways has become increasingly important. Existing ti…
Beyond Magnitude and Shape: A Direction-Aware Loss for Time Series Forecasting
Seunghan Lee, Jaehoon Lee, Jun Seo +9
The direction of change --- whether a series will move up or down --- is often as important as its exact value in decisiondriven applications such as risk management and financial…
Channel-wise Retrieval for Multivariate Time Series Forecasting
Junhyeok Kang, Jun Seo, Soyeon Park +4
Multivariate time series forecasting often struggles to capture long-range dependencies due to fixed lookback windows. Retrieval-augmented forecasting addresses this by retrieving…