Natalia Díaz Rodríguez

Claims that LLMs lack genuine reasoning based on the GSM-Symbolic benchmark are likely overstated, as many reported performance drops disappear under more rigorous statistical scrutiny and when controlling for dataset distributional shifts.

Discarded classification weights from pre-trained vision models can be resurrected as powerful semantic prototypes, unlocking zero-shot vision-language alignment and boosting cross-modal performance.