arXiv (All)
open access
Active Adaptation, Not Static Defense: Temporal Dynamics of Preventative Steering in Adversarial Fine-Tuning
Large language models remain fragile against malicious fine-tuning, motivating training-time defenses against harmful persona drift. Preventative Steering injects undesirable-trait persona vectors during fine-tuning and removes them at evaluation time, yet the mechanism behind its lasting protection
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
- Watch your steps: Dormant Adversarial Behaviors that Activate upon LLM Finetuning#799861
- Adversarial Reframing: A Framework for Targeted Generation in Language Models#216742
- Efficient LLM Adversarial Training via Low-Rank Defense and Circuit-Guided Surrogates#1116390
- PHANTOM: A Large-Scale Dataset of Multimodal Adversarial Attacks for Vision-Language Models#303213
- Hearing the Whispers: Black-Box Membership Inference Attacks on Finetuned TTS Models#822153
Record · ID 997055
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
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
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive