JAM discovers theory-invariant pseudo-facets via attention-pooled graph prototypical networks, Cross-Theory Harmonization, and LLM-as-a-Judge, improving cross-framework balanced accuracy on Essays and Kaggle datasets.
Cross-lingual attention distillation with personality-informed generative augmentation for multilingual personality recognition,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Large-Language-Models-as-a-Judge in Theory-Agnostic Adaptive Metric-Alignment for Prototypical Networks in Personality Recognition
JAM discovers theory-invariant pseudo-facets via attention-pooled graph prototypical networks, Cross-Theory Harmonization, and LLM-as-a-Judge, improving cross-framework balanced accuracy on Essays and Kaggle datasets.