Sign inGet started
Paper · arXiv

RELATE: An Evaluation Framework for measuring Relational Orientation of Large Language Models

Large language models (LLMs) are increasingly used for emotional support, raising concern that sustained use may draw users away from their real-world relationships. Yet existing evaluations primarily focus on the safety, empathy, or helpfulness of responses, leaving under-examined a relational question: where does the model orient the user for continued support? To address this question, we introduce relational orientation, a property operationalized through two non-exclusive dimensions: inward-facing (IF) language, which positions the AI as the user's ongoing source of support, and outward-scaffolding (OS) language, which encourages real-world human connection. Grounded in psychological...

AuthorsShivam Shukla, Jihye Kim, Shubham Gaur et al.
Primary categorycs.CL
Published7 October 2026
Last updated at source7 October 2026
cs.CL
Embed this entry
<iframe src="https://silytics.si/embed/item/9c72bc64-195d-43bd-8deb-c9ba9eeb8324" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 2 days

0 now. Counts as reported by the source, snapshotted daily by Silytics.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.