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Adaptive Rubric-Skill Co-Evolution (ARISE), a reinforcement learning framework that uses rollout evidence to continually adapt evaluation criteria, exploration guidance, and training priorities, and demonstrates that ARISE successfully enhances both overall task performance and training efficiency.
JointScaler is proposed, a learning-based framework for multi-indicator distribution forecasting and uncertainty-aware scaling that captures inter-indicator dependencies via hierarchical attention, models dynamic uncertainties with normalizing flows, and leverages full predictive distributions to optimize bundled resou...
KairosAgent, a novel agentic framework for multimodal time series forecasting, including an LLM-based reasoner and a TSFM-based forecaster, unifies textual reasoning and numerical forecasting by dynamically invoking analytical tools to enhance the numerical understanding and semantic reasoning capabilities of LLMs.
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