From the 1 of 9 linked papers with an AI index.
4 papers · 1 filter
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…
Rethinking Multimodal Fusion for Time Series: Text Modalities Need Constrained Fusion
Seunghan Lee, Jun Seo, Jaehoon Lee +7
The paper investigates how naive multimodal fusion can hurt time series forecasting performance and proposes a Controlled Fusion Adapter that uses low‑rank adapters to filter irrel…
Adaptive Information Routing for Multimodal Time Series Forecasting
Jun Seo, Hyeokjun Choe, Seohui Bae +10
Time series forecasting is a critical task for artificial intelligence with numerous real-world applications. Traditional approaches primarily rely on historical time series data t…