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This paper presents an AI-powered, culturally aware chatbot for stress detection and wellness support among Pakistani university students, using Random Forest for classification with 89.09% accuracy and integrating an open-source LLM for conversational support.
This paper presents the DFKI-MLT system for SemEval-2026 Task 7 on cultural awareness, which applies activation steering to multilingual LLMs using language vectors from parallel FLORES data. The system achieved 86.96% accuracy in the MCQ track, ranking 7th out of 17 teams, and post-hoc analyses reveal that gains are layer-sensitive and vary across language-region pairs.