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Author

María Pérez-Ortiz

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#artificial intelligence May 2026

Tool Calling is Linearly Readable and Steerable in Language Models

The model's hidden state provides a way to read, steer, and check tool choice before a call is made, suggesting that the model's hidden state provides a way to read, steer, and check tool choice before a call is made.

Ze-Kun Wu, Ze-Kun Wang, Seonglae Cho et al. · 11 citations · ⚡2
Jul 2026

Training Large Language Models for Self-Explanation Faithfulness

It is shown that models can be trained to implicitly identify influential factors and disclose them, offering a scalable path toward reducing unfaithful reasoning in LLMs.

Y. Cheah, María Pérez-Ortiz, N. Siegel et al. · 0 citations

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