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Author

Dongwan Kang

Observed name: Kang, Dongwan
Observed institution: LG AI Research (South Korea)
ORCID: 0009-0006-5390-5526
Observed ORCID: 0009-0006-5390-5526
OpenAlex ID: A5129680381
Not All Retrievals are Useful: Cross-Attention for Input-Aware RAG in Time Series Forecasting
2026 · Lee, Seunghan, Lee, Jaehoon, et al. · arXiv (Cornell University) · 5
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EXAONE Finance 1.0: An Attention-free Time Series Foundation Model for Financial Time Series
2026 · Lee, Seunghan, Lee, Jaehoon, et al. · arXiv (Cornell University) · 4
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Beyond Magnitude and Shape: A Direction-Aware Loss for Time Series Forecasting
2026 · Lee, Seunghan, Lee, Jaehoon, et al. · arXiv (Cornell University) · 4
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Rethinking Multimodal Fusion for Time Series: Text Modalities Need Constrained Fusion
2026 · Lee, Seunghan, Seo, Jun, et al. · arXiv (Cornell University) · 3
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FinVerse: Toward More Realistic Evaluation for Financial Time-Series Forecasting
2026 · Lee, Jaehoon, Seo, Jun, et al. · arXiv (Cornell University) · 2
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FinSTaR: Towards Financial Reasoning with Time Series Reasoning Models
2026 · Seunghan Lee, Jun Seo, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 2
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PALM: Point-in-Time Adaptation for Financial Language Models
2026 · Lee, Seunghan, Seo, Jun, et al. · arXiv (Cornell University) · 1
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EXAONE Demand 1.0: A Time Series Foundation Model for Demand Forecasting
2026 · Lee, Seunghan, Han, Sangjun, et al. · arXiv (Cornell University)
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Explaining Time Series Forecasting with Horizon-Resolved Attribution
2026 · Lee, Seunghan, Seo, Jun, et al. · arXiv (Cornell University)
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FinTexTS: Financial Text-Paired Time-Series Dataset via Semantic-Based and Multi-Level Pairing
2026 · Jaehoon Lee, Suhwan Park, et al. · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
ReasonCast: Towards Explainable Time Series Forecasting with Reasoning
2026 · Lee, Seunghan, Seo, Jun, et al. · arXiv (Cornell University)
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AdaTKG: Adaptive Memory for Temporal Knowledge Graph Reasoning
2026 · Lee, Seunghan, Seo, Jun, et al. · arXiv (Cornell University)
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Additional file 4: of Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes
2015 · Kim, SungHwan, Herazo-Maya, Jose, et al. · Figshare
Additional file 1: of Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes
2015 · Kim, SungHwan, Herazo-Maya, Jose, et al. · Figshare
Additional file 5: of Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes
2015 · Kim, SungHwan, Herazo-Maya, Jose, et al. · Figshare
Works count: 15
Citation count: 21
H-index: 3
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