PsyGAT structures conversations as dynamic temporal graphs with Psychological Expression Units and persona augmentation to reach state-of-the-art Macro F1 scores of 89.99 and 71.37 on DAIC-WoZ and E-DAIC while adding causal interpretability.
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SDialog is a Python toolkit that unifies dialog generation, evaluation, mechanistic interpretability, and audio simulation for building and analyzing LLM-based conversational agents.
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Psychologically-Grounded Graph Modeling for Interpretable Depression Detection
PsyGAT structures conversations as dynamic temporal graphs with Psychological Expression Units and persona augmentation to reach state-of-the-art Macro F1 scores of 89.99 and 71.37 on DAIC-WoZ and E-DAIC while adding causal interpretability.
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SDialog: A Python Toolkit for End-to-End Agent Building, User Simulation, Dialog Generation, and Evaluation
SDialog is a Python toolkit that unifies dialog generation, evaluation, mechanistic interpretability, and audio simulation for building and analyzing LLM-based conversational agents.