ReLaMix: Residual Latency-Aware Mixing for Delay-Robust Financial Time-Series Fo

arXiv:2609.11206v1 Announce Type: new Abstract: Cryptocurrency forecasting presents a distinctive combination of extreme cross-asset scale heterogeneity, non-stationary dynamics,

arXiv:2604.05364v1 Announce Type: new Abstract: We introduce TFRBench, the first benchmark designed to evaluate the reasoning capabilities of forecasting systems. Traditionally,

arXiv:2603.22305v1 Announce Type: cross Abstract: Large Language Models (LLMs) are rapidly transitioning from static Natural Language Processing (NLP) tasks including sentiment

arXiv:2603.18712v1 Announce Type: new Abstract: The task of multi-channel time series forecasting is ubiquitous in numerous fields such as finance, supply chain management, and

arXiv:2603.19136v1 Announce Type: cross Abstract: Stock markets exhibit regime-dependent behavior where prediction models optimized for stable conditions often fail during