Search Results for author: Fernando Sánchez-Vega

Found 3 papers, 1 papers with code

DAIC-WOZ: On the Validity of Using the Therapist's prompts in Automatic Depression Detection from Clinical Interviews

no code implementations22 Apr 2024 Sergio Burdisso, Ernesto Reyes-Ramírez, Esaú Villatoro-Tello, Fernando Sánchez-Vega, Pastor López-Monroy, Petr Motlicek

Finally, to highlight the magnitude of this bias, we achieve a 0. 90 F1 score by intentionally exploiting it, the highest result reported to date on this dataset using only textual information.

Depression Detection

Adaptive Cross-lingual Text Classification through In-Context One-Shot Demonstrations

1 code implementation3 Apr 2024 Emilio Villa-Cueva, A. Pastor López-Monroy, Fernando Sánchez-Vega, Thamar Solorio

Zero-Shot Cross-lingual Transfer (ZS-XLT) utilizes a model trained in a source language to make predictions in another language, often with a performance loss.

text-classification Text Classification +1

A visual approach for age and gender identification on Twitter

no code implementations28 May 2018 Miguel A. Alvarez-Carmona, Luis Pellegrin, Manuel Montes-y-Gómez, Fernando Sánchez-Vega, Hugo Jair Escalante, A. Pastor López-Monroy, Luis Villaseñor-Pineda, Esaú Villatoro-Tello

The goal of Author Profiling (AP) is to identify demographic aspects (e. g., age, gender) from a given set of authors by analyzing their written texts.

Marketing

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