Conceptio › Archive › arXiv (All)
arXiv (All) open access

Narrow Multimodal Fine-Tuning Can Induce Emergent Misalignment

Liu, Shunchang et al.
arXiv (All) · Papers
Open Source ↗Direct PDF ↓
computer-vision-and-pattern-recognitionmachine-learning
Modern AI models are aligned through post-training to adapt them to downstream tasks. Recent work shows that fine-tuning language models on narrow tasks can induce emergent misalignment (EM), causing broadly harmful behaviors beyond the training task. However, EM has been studied almost entirely in
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1129884
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive