When and How Human Curation Backfires: Preference Alignment under Multi-Model Self-Consuming Loop
Foundation models are increasingly trained on synthetic data generated by prior model iterations rather than exclusively on real data. This self-consuming training paradigm can lead to model collapse, divergence, or bias amplification. Recent work (Ferbach et al., 2024) shows that incorporating human curation into the loop can steer a self-consuming model toward human-aligned behavior, but these analyses focus on a single, isolated model that solely consumes its own outputs. In practice, however
Record details
Published: 28 May 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Safety & alignment
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Isolating LLM Lexical Bias: A Curation-Free Triangulated Metric for Preference-Stage Learning
arXiv · 29 May 2026
Algorithmic Fragility and Persona Bias in LLM-Generated Autistic Communication
arXiv · 26 May 2026
Improving Visual Representation Alignment Generation with GRPO
arXiv · 30 May 2026
DeGRe: Dense-supervised Generative Reranking for Recommendation
arXiv · 25 May 2026
Silent Failures in Federated Personalization of Foundation Models
arXiv · 31 May 2026
Language Bias in LVLMs: From In-Depth Analysis to Simple and Effective Mitigation
arXiv · 24 May 2026
How to cite this record
ethics.ai (28 May 2026), “When and How Human Curation Backfires: Preference Alignment under Multi-Model Self-Consuming Loop,” evidence record 3543, https://ethics.ai/record/3543 (originally published by arXiv).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.