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cs.LG2026
CTRL: Control-Based Time Series Forecasting with LLM-Guided Residual Learning
Minkyoung Kim, Daeun Ji, Yohan Lee +2
Time series forecasting underpins critical decision-making across diverse domains. While large language models (LLMs) offer promising reasoning capabilities, existing LLM-based tim…
cs.LG2026
Beyond Similarity: Coverage-Aware Prompt Selection for Time Series Forecasting with LLMs
Daeun Ji, Minkyoung Kim, Dongkuk Kim +3
Similarity-based retrieval is the dominant rule for conditioning large language models (LLMs) in in-context learning, retrieval-augmented generation, and prompt-based time series f…
cs.LG2026
Bilevel Graph Structure Learning, Revisited: Inner-Channel Origins of the Reported Gain
Minkyoung Kim, Beakcheol Jang
Bilevel graph structure learning is widely understood to improve graph neural networks by jointly optimizing model parameters and a learned graph structure, with the resulting perf…