Sign inGet started
Paper · arXiv

From Encoding to Generation: Towards Empathetic Large Language Models

Empathetic interaction involves two distinguishable capacities: representing another person's emotional state (cognitive empathy) and generating an appropriate response to that state (affective empathy). We apply this distinction to examine how emotion-related information is internally organized, selectively attended to, and carried through response generation in Llama-3.2-3B-Instruct across 10 emotion categories from the EmpatheticDialogues dataset. Layer-wise linear probing revealed a broad middle-layer region of peak emotion-category decodability, with the layer-11 L2 probe achieving 63.6% held-out accuracy against a 10% chance level and a 54.6% TF-IDF lexical baseline. During response...

AuthorsSamhita Bollepally, Takashi Yamauchi, Marissa West
Primary categorycs.AI
Published20 October 2026
Last updated at source20 October 2026
cs.AI
Embed this entry
<iframe src="https://silytics.si/embed/item/be4edc89-80ac-4ff0-a2ac-f234f74ef6df" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 21 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.