activity
20242026
collaborators

6 papers

cs.LG2026

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…

cs.AI2026

Traceable Multi-Agent System for Knowledge-Based Forecasting

Junhyeok Kang, Sangjun Han, Hyeokjun Choe +1

Enterprise forecasting increasingly relies on autonomous agents that interpret documents, search for data, generate code, and revise models. While this autonomy helps build adaptiv…

cs.AI2026

ReasonCast: Towards Explainable Time Series Forecasting with Reasoning

Seunghan Lee, Jun Seo, Jaehoon Lee +9

Most time series (TS) models are specialized for a single task, either understanding (i.e., returning text answers about a TS) or generation (i.e., returning a numeric forecast). O…

cs.LG2026

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…

cs.LG2025

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…

cs.SD2024

Flexible Control in Symbolic Music Generation via Musical Metadata

Sangjun Han, Jiwon Ham, Chaeeun Lee +7

In this work, we introduce the demonstration of symbolic music generation, focusing on providing short musical motifs that serve as the central theme of the narrative. For the gene…