Self-Anchoring Calibration Drift in Large Language Models: How Multi-Turn Conversations Reshape Model Confidence
Harshavardhan

TL;DR
This study investigates how large language models' confidence levels change during multi-turn conversations, revealing complex, model-specific calibration drift patterns that challenge previous assumptions about model confidence stability.
Contribution
The paper introduces the concept of Self-Anchoring Calibration Drift (SACD) and provides an empirical analysis of its effects across multiple state-of-the-art LLMs in various domains.
Findings
Claude Sonnet 4.6 shows decreased confidence with self-anchoring.
GPT-5.2 exhibits increased confidence and calibration error escalation.
Gemini 3.1 Pro's calibration error remains stable under self-anchoring.
Abstract
We introduce Self-Anchoring Calibration Drift (SACD), a hypothesized tendency for large language models (LLMs) to show systematic changes in expressed confidence when building iteratively on their own prior outputs across multi-turn conversations. We report an empirical study comparing three frontier models -- Claude Sonnet 4.6, Gemini 3.1 Pro, and GPT-5.2 -- across 150 questions spanning factual, technical, and open-ended domains, using three conditions: single-turn baseline (A), multi-turn self-anchoring (B), and independent repetition control (C). Results reveal a complex, model-heterogeneous pattern that partially diverges from pre-registered hypotheses. Claude Sonnet 4.6 exhibited significant decreasing confidence under self-anchoring (mean CDS = -0.032, t(14) = -2.43, p = .029, d = -0.627), while also showing significant calibration error drift (F(4,56) = 22.77, p < .001, eta^2 =…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTopic Modeling · Neurobiology of Language and Bilingualism · Language and cultural evolution
