Paper

The AI Epistemic Deference Index: A Continuous Measure of Sycophancy

Unreadunread

AI summary

arXiv:2606. 07897v1 Announce Type: new Abstract: Current AI models frequently exhibit epistemic sycophancy, endorsing claims to agree with a user.

Reading status

Priority

About this paper

Authors: Alejandro Botas, Paul de Font-Reaulx, Luke Hewitt
Released: 2026-06-09 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because The AI Epistemic Deference Index: A Continuous Measure of Sycophancy overlaps with clean result "Only continuous soft prefixes hit both EM axes at once on Qwen-2.5-7B-Instruct: discrete prompt searches split between the alignment objective and the distributional objective, and both discretizations of the soft prefix collapse (MODERATE confidence)", clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)", experiment "#351 follow-up: broader-vocab position-0 sweep at T=1.0 + position-1 suffix isolation". Matching terms: eval, line, rate, position, test, language, model. Source: arxiv cs.AI (Artificial Intelligence).
arXiv: 2606.07897

Ask Claude about this paper

Posts a comment with @claude so the runner spins up a Claude Code session scoped to The AI Epistemic Deference Index: A Continuous Measure of Sycophancy. Replies appear in the conversation below.

Comments

No comments yet.

Related records

No links yet.