multi-attribute-steering

MAT-Steer introduces a novel inference-time intervention framework for steering LLMs across multiple conflicting attributes by learning sparse, orthogonal steering vectors that selectively target tokens relevant to each attribute, achieving gains in QA tasks and generative tasks over prior methods.