arXiv (All)
open access
Does Steering Break Your Model? A Multi-Dimensional Evaluation Suite for LLM Steering Methods
Activation steering provides a lightweight and flexible way to control large language model (LLM) behavior. However, effective steering requires more than inducing the intended behavior: it should also limit unintended changes and remain robust across inputs and training data. Existing evaluations c
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
- Beyond Corrected Actions: Training LLM Agents on Textual Critiques#1345190
- EasySteer: A Unified Framework for High-Performance and Extensible LLM Steering#926966
- Toward Latent Language Model Skills Steering and Optimization: An Empirical Study#794243
- Toward Latent Language Model Skills Steering and Optimization: An Empirical Study#790224
- Experience Funnel: A State-Policy Alternating Loop for Self-Evolving Agents#986540
Record · ID 1217097
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