Controlling Tool Use with Heading-Specific Activation Steering

arXiv:2511.21399v3 Announce Type: replace-cross Abstract: Activation steering -- adding a vector to a model's residual stream to modify its behavior -- is widely used in safety

arXiv:2605.14038v1 Announce Type: new Abstract: Large language models (LLMs) increasingly act as autonomous agents that must decide when to answer directly vs. when to invoke

arXiv:2609.25678v1 Announce Type: new Abstract: Large language model (LLM) agents must generalize from tools seen during training to unseen tools at deployment. A key challenge is

arXiv:2605.06890v1 Announce Type: new Abstract: AI agents are promising for high-stakes enterprise workflows, but dependable deployment remains limited because tool-use failures

arXiv:2605.00136v1 Announce Type: new Abstract: Tool-augmented reasoning has become a popular direction for LLM-based agents, and it is widely assumed to improve reasoning and

arXiv:2610.24367v1 Announce Type: new Abstract: Activation steering provides a lightweight alternative to fine-tuning for controlling large language model behavior. Existing

arXiv:2610.24287v1 Announce Type: new Abstract: Search-augmented language models increasingly serve as long-horizon research agents, yet most open training methods assume a fixed

arXiv:2608.06578v1 Announce Type: new Abstract: Frontier language models are trained using distinct data, objectives, and safety pipelines. Whether these differences produce