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Capturing the nuances of problem-solving stages with a reasoning LM unlocks significant gains in knowledge tracing accuracy, particularly as learners engage more deeply with the material.
Channel-specific historical data retrieval boosts multivariate time series forecasting accuracy, finally accounting for the fact that different variables have different rhythms.
Stop relying on keyword matching: FinTexTS uses semantic similarity and LLM-driven multi-level classification to pair financial text with time-series data, boosting stock price prediction.
