IndicBERT-HPA with language-aware adapters and verification-guided deferral outperforms baselines on multilingual orthopedic note classification, reaching 0.8792 Macro-F1 overall and 84.4% selective accuracy at 72.3% coverage.
Morley, and Luis Filipe Nakayama
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Modifying nationality and language parameters in English-centric personas for mental health dialogues introduces clinical inconsistencies across languages and causes LLM judges to perform inaccurately on non-English depression severity assessments.
citing papers explorer
-
Reliable Multilingual Orthopedic Decision Support from Clinical Narratives: Language-Aware Adaptation and Verification-Guided Deferral
IndicBERT-HPA with language-aware adapters and verification-guided deferral outperforms baselines on multilingual orthopedic note classification, reaching 0.8792 Macro-F1 overall and 84.4% selective accuracy at 72.3% coverage.
-
Creating Multilingual Mental Health Dialogue Datasets: Limits of Persona-Based Localization via Nationality and Language
Modifying nationality and language parameters in English-centric personas for mental health dialogues introduces clinical inconsistencies across languages and causes LLM judges to perform inaccurately on non-English depression severity assessments.