#steering News & Analysis

3 articles tagged with #steering. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBullisharXiv – CS AI · May 117/10

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Tool Calling is Linearly Readable and Steerable in Language Models

Researchers discovered that language models encode tool-selection decisions in interpretable linear patterns within their internal activations, enabling both prediction of errors before execution and steering of tool choices at 77-100% accuracy. This finding has implications for making AI agents more reliable and controllable, particularly in high-stakes scenarios where wrong tool selection causes irreversible failures.

🧠 Llama

AINeutralarXiv – CS AI · Mar 46/102

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How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities

Researchers introduce SteerEval, a new benchmark for evaluating how controllable Large Language Models are across language features, sentiment, and personality domains. The study reveals that current steering methods often fail at finer-grained control levels, highlighting significant risks when deploying LLMs in socially sensitive applications.

AINeutralarXiv – CS AI · Apr 146/10

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Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics

Researchers present a unified framework for understanding how different methods control large language models—including fine-tuning, LoRA, and activation interventions—revealing a fundamental trade-off between steering strength and output quality. The analysis explains this through an activation manifold perspective and introduces SPLIT, a new steering method that improves control while better preserving model coherence.