Source record

Published by arXiv cs.HC (T1 source). The original is at https://arxiv.org/abs/2608.24224.

Pipeline notes

The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.

Aura is a framework that estimates user emotional state from facial expressions, uses a probabilistic belief model to select interventions, and applies LoRA adapters to modulate LLM output mid-turn. A within-subjects study (N=20) on information-seeking tasks reported higher normalized perceived learning gains than a Llama-3 baseline and 21% lower interaction time versus GPT-4o and Llama-3 baselines.

Concrete architecture and measured interaction-time gains for real-time emotion-aware LLM adaptation, relevant to designing responsive agent workflows that adjust mid-turn rather than between turns.

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