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LLMs can significantly boost forecasting accuracy, but their effectiveness is hampered by measurement limitations and sensitivity to input changes.
Agents struggle to act effectively in 3D scenes, with none of the eleven evaluated VLMs achieving consistent performance across diverse tasks.
Tool-based reasoning in IQA-T1 leads to significant improvements in image quality assessments, outperforming traditional methods while enhancing interpretability.
