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EXAONE Tabular outperforms tuned ensembles and larger models, achieving top rankings in multiple benchmarks while drastically reducing inference costs.
Strong performance on generic forecasting metrics can be misleading, as FinVerse reveals that it often fails to translate into effective financial decision-making.
ReasonCast achieves unprecedented integration of time series forecasting and self-explanation, outperforming traditional models while providing causal insights in a single response.
Agents in PCBWorld can achieve near rule-based performance in PCB routing, showcasing the power of interactive, engine-grounded learning.
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.
