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cs.CL2025
EmoGist: Efficient In-Context Learning for Visual Emotion Understanding
Ronald Seoh, Dan Goldwasser
In this paper, we introduce EmoGist, a training-free, in-context learning method for performing visual emotion classification with LVLMs. The key intuition of our approach is that…
cs.CL2025
SOLAR: Towards Characterizing Subjectivity of Individuals through Modeling Value Conflicts and Trade-offs
Younghun Lee, Dan Goldwasser
Large Language Models (LLMs) not only have solved complex reasoning problems but also exhibit remarkable performance in tasks that require subjective decision making. Existing stud…
cs.CL2024
Towards Understanding Counseling Conversations: Domain Knowledge and Large Language Models
Younghun Lee, Dan Goldwasser, Laura Schwab Reese
Understanding the dynamics of counseling conversations is an important task, yet it is a challenging NLP problem regardless of the recent advance of Transformer-based pre-trained l…