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            <namePart type="given">Guillermo</namePart>
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    <abstract>In this work, we address the detection of drug abuse repercussions in Reddit posts, as part of SMM4H-HeaRD Task 7: Extraction of Social and Clinical Impacts of Substance Use from Social Media Posts. We evaluate multiple approaches, including fine-tuning and zero-shot inference, across several deep learning architectures. Our best result is obtained using an adapter-based fine-tuning approach on the DeBERTaV3 model. In addition, we explore text-based evolutionary optimization for Gemma 4 workflows and show that, on this task, they achieve competitive performance with the supervised DeBERTaV3 setup.</abstract>
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%0 Conference Proceedings
%T RACAI at #SMM4H-HeaRD: Named Entity Recognition for Detecting the Impacts of Drug Abuse in Social Media Posts: Zero-Shot and Fine-Tuning Approaches
%A Boros, Tiberiu
%A Chivereanu, Radu-Gabriel
%Y Lopez-Garcia, Guillermo
%Y Gonzalez-Hernandez, Graciela
%S Proceedings of the 11th Social Media Mining for Health Research and Applications (SMM4H-HeaRD 2026) Workshop and Shared Tasks
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, United States
%@ 979-8-89176-432-3
%F boros-chivereanu-2026-racai
%X In this work, we address the detection of drug abuse repercussions in Reddit posts, as part of SMM4H-HeaRD Task 7: Extraction of Social and Clinical Impacts of Substance Use from Social Media Posts. We evaluate multiple approaches, including fine-tuning and zero-shot inference, across several deep learning architectures. Our best result is obtained using an adapter-based fine-tuning approach on the DeBERTaV3 model. In addition, we explore text-based evolutionary optimization for Gemma 4 workflows and show that, on this task, they achieve competitive performance with the supervised DeBERTaV3 setup.
%U https://aclanthology.org/2026.smm4h-1.20/
%P 121-126

Markdown (Informal)

[RACAI at #SMM4H-HeaRD: Named Entity Recognition for Detecting the Impacts of Drug Abuse in Social Media Posts: Zero-Shot and Fine-Tuning Approaches](https://aclanthology.org/2026.smm4h-1.20/) (Boros & Chivereanu, SMM4H 2026)

• RACAI at #SMM4H-HeaRD: Named Entity Recognition for Detecting the Impacts of Drug Abuse in Social Media Posts: Zero-Shot and Fine-Tuning Approaches (Boros & Chivereanu, SMM4H 2026)

ACL

• Tiberiu Boros and Radu-Gabriel Chivereanu. 2026. RACAI at #SMM4H-HeaRD: Named Entity Recognition for Detecting the Impacts of Drug Abuse in Social Media Posts: Zero-Shot and Fine-Tuning Approaches. In Proceedings of the 11th Social Media Mining for Health Research and Applications (SMM4H-HeaRD 2026) Workshop and Shared Tasks, pages 121–126, San Diego, United States. Association for Computational Linguistics.