MSTN introduces a lightweight multi-scale temporal network using convolutional encoding, recurrent or attention-based modeling, and gated fusion to achieve claimed state-of-the-art results on 21 of 27 time series benchmarks while using under 1.1M parameters and fast inference.
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cs.LG 2years
2025 2verdicts
UNVERDICTED 2representative citing papers
LLM4Delay improves flight delay prediction accuracy by using instance-level projection to adapt LLMs for integrating textual aeronautical information with multiple aircraft trajectories.
citing papers explorer
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MSTN: A Lightweight and Fast Model for General TimeSeries Analysis
MSTN introduces a lightweight multi-scale temporal network using convolutional encoding, recurrent or attention-based modeling, and gated fusion to achieve claimed state-of-the-art results on 21 of 27 time series benchmarks while using under 1.1M parameters and fast inference.
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LLM4Delay: Flight Delay Prediction via Cross-Modality Adaptation of Large Language Models and Aircraft Trajectory Representation
LLM4Delay improves flight delay prediction accuracy by using instance-level projection to adapt LLMs for integrating textual aeronautical information with multiple aircraft trajectories.