Exploring LLM Emotional States and Runtime Intervention
sloppenheimer · x · 2026-07-15
The author proposes a vision where future research uncovers how a model's internal "emotional state" impacts its performance on real-world tasks. This could pave the way for runtime intervention techniques, such as dynamically applying LoRA or injecting steering vectors during a single session to adjust model behavior and output in real time.
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