Entity · technique

Cross-Theory Harmonization

techniqueactiveprovisionalcross-theory-harmonization-a95fff01·1 events·first seen 3h ago

Aliases: Cross-Theory Harmonization

Co-occurring entities

Large-Language-Models-as-a-Judge in Theory-Agnostic Adaptive Metric-Alignment for Prototypical Networks in Personality Recognition JAM (Judge for Adaptive Metric-Alignment)

More like this (12)

Unified Harm Framework Cross-Domain Transfer Tri-System Theory ML Alignment & Theory Scholars Program Contrastive-Difference CKA Reveals Concept-Specific Structural Alignment Across Language Model Architectures Matching Principle Consensus-based Agentic Large Language Model Framework for Harmonized Tariff Schedule Code Classification Cross-Annotator Preference Optimization (CAPO)Consistency Training Can Entrench Misalignment MetaSyn Bridging Talk and Thought: Understanding Dialogue Dynamics Across Collaborative Problem-Solving Contexts Creative Quality Alignment (CQA)

Recent events (1)

4arXiv · cs.CL·3h ago·source ↗

JAM: LLM-as-a-Judge framework for theory-agnostic personality recognition via prototypical networks

Researchers introduce JAM (Judge for Adaptive Metric-Alignment), a framework for personality recognition that avoids dependence on predefined psychological taxonomies like Big Five or MBTI. The system uses an Attention-Pooled Graph Prototypical Network with a Cross-Theory Harmonization approach to unify heterogeneous personality datasets, and incorporates an LLM-as-a-Judge mechanism in two configurations to identify ambiguous training samples and guide metric learning. Experiments show improved cross-framework generalization, with the approach enabling inference of latent psychological profiles from text without theory-specific labels.

Evaluation and Benchmarking Cross-Theory Harmonization Large-Language-Models-as-a-Judge in Theory-Agnostic Adaptive Metric-Alignment for Prototypical Networks in Personality Recognition JAM (Judge for Adaptive Metric-Alignment)