SAGE: A Strategy-Aware Graph-Enhanced Generation Framework For Online Counseling
Effective mental health counseling is a complex, theory-driven process requiring the simultaneous integration of psychological frameworks, real-time distress signals, and strategic intervention planning. This level of clinical reasoning is critical for safety and therapeutic effectiveness but is often missing in general-purpose Large Language Models (LLMs). We introduce SAGE (Strategy-Aware Graph-Enhanced), a novel framework designed to bridge the gap between structured clinical knowledge and generative AI. SAGE constructs a heterogeneous graph that unifies conversational dynamics with a psychologically grounded layer, explicitly anchoring interactions in a theory-driven lexicon. Our arch...
| Authors | Eliya Naomi Aharon, Meytal Grimland, Avi Segal et al. |
|---|---|
| Primary category | cs.CL |
| Published | 29 April 2026 |
| Last updated at source | 29 April 2026 |
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