SteeringControl: Holistic Evaluation of Alignment Steering in LLMs
We introduce SteeringControl, a benchmark for evaluating representation
steering methods across core alignment objectives--bias, harmful generation,
and hallucination--and their effects on secondary behaviors such as sycophancy
and commonsense morality. While prior alignment work often highlights
truthfulness or reasoning ability to demonstrate the side effects of
representation steering, we find there are many unexplored tradeoffs not yet
understood in a systematic way. We collect a dataset of safety-relevant primary
and secondary behaviors to evaluate steering effectiveness and behavioral
entanglement centered around five popular steering methods. To enable this, we
craft a modular steering framework based on unique components that serve as the
building blocks of many existing methods. Our results on Qwen-2.5-7B and
Llama-3.1-8B find that strong steering performance is dependent on the specific
combination of steering method, model, and targeted behavior, and that severe
concept entanglement can result from poor combinations of these three as well.
We release our code here:
https://github.com/wang-research-lab/SteeringControl.git.
68cb65745a7803ff3be42d04
Vincent Siu
68cb65745a7803ff3be42d05
Nicholas Crispino
claimed_verified
2025-09-18T13:27:17.164Z
63c73584f3f2499604a418c3
/avatars/3b48a2d41631ae853bb0e3c5b92af773.svg
Nicholas Crispino
user
ncrispino
68cb65745a7803ff3be42d06
David Park
68cb65745a7803ff3be42d07
Nathan W. Henry
68cb65745a7803ff3be42d08
Zhun Wang
68cb65745a7803ff3be42d09
Yang Liu
68cb65745a7803ff3be42d0a
Dawn Song
68cb65745a7803ff3be42d0b
Chenguang Wang
SteeringControl: Holistic Evaluation of Alignment Steering in LLMs
We introduce SteeringControl, a benchmark for evaluating representation
steering methods across core alignment objectives--bias, harmful generation,
and hallucination--and their effects on secondary behaviors such as sycophancy
and commonsense morality. While prior alignment work often highlights
truthfulness or reasoning ability to demonstrate the side effects of
representation steering, we find there are many unexplored tradeoffs not yet
understood in a systematic way. We collect a dataset of safety-relevant primary
and secondary behaviors to evaluate steering effectiveness and behavioral
entanglement centered around five popular steering methods. To enable this, we
craft a modular steering framework based on unique components that serve as the
building blocks of many existing methods. Our results on Qwen-2.5-7B and
Llama-3.1-8B find that strong steering performance is dependent on the specific
combination of steering method, model, and targeted behavior, and that severe
concept entanglement can result from poor combinations of these three as well.
We release our code here:
https://github.com/wang-research-lab/SteeringControl.git.
SteeringControl evaluates representation steering methods across bias, harmful generation, and hallucination, revealing tradeoffs and entanglement effects on secondary behaviors like sycophancy and commonsense morality.
representation steering bias harmful generation hallucination sycophancy commonsense morality steering effectiveness behavioral entanglement modular steering framework concept entanglement Qwen-2.5-7B Llama-3.1-8B