Bowen Liu

MoFE not only mitigates phase-lag effects in cryptocurrency forecasting but also translates its predictive edge into substantial trading profits.

Current models may excel in accuracy but often fail to ground their predictions in the visual evidence, with GPT-5.6 achieving only 3.93% QExact despite a seemingly high overall accuracy.

LLMs consistently underperform in shared-budget reasoning tasks, revealing a critical gap between their single-task capabilities and multi-task resource allocation.

AI agents may ace endpoint identification but falter in delivering the evidence-based diagnostics essential for real-world telecom troubleshooting.