antbaez.github.io/research.html at main · antbaez/antbaez.github.io · GitHub

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              <p>
                <a href="https://arxiv.org/abs/2605.15455" target="_blank"><b>Multi-Turn Neural Transparency: Surfacing Neural Activations Improves User Calibration to LLM Behavioral Drift</b></a>
                <br>
                Sheer Karny*, <b>Anthony Baez</b>*, and Pat Pataranutaporn
                <br>
                <i>*Equal Contribution</i>
                <br>
                <i>Under Review</i>
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                <a href="https://arxiv.org/pdf/2511.00230" target="_blank"><b>Neural Transparency: Mechanistic Interpretability Interfaces for Anticipating Model Behaviors for Personalized AI</b></a>
                <br>
                Sheer Karny*, <b>Anthony Baez</b>*, and Pat Pataranutaporn
                <br>
                <i>*Equal Contribution</i>
                <br>
                <i>ACM Conference on Intelligent User Interfaces 2026</i>
                <br>
                <a href="https://github.com/mitmedialab/neural-transparency" target="_blank">Code</a>
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              <p>
                <a href="https://arxiv.org/pdf/2511.09048" target="_blank"><b>Guaranteeing Conservation of Integrals in Physics-Informed Neural Networks</b></a>
                <br>
                <b>Anthony Baez</b>, Wang Zhang, Ziwen Ma, Subhro Das, Lam M Nguyen, and Luca Daniel
                <br>
                <i>Arxiv Preprint</i>
                <br>
                <a href="https://github.com/antbaez/pinn-proj" target="_blank">Code</a>
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              <p>
                <a href="https://arxiv.org/abs/2410.17445" target="_blank"><b>Guaranteeing Conservation Laws in Physics-Informed Neural Networks</b></a>
                <br>
                <b>Anthony Baez</b>, Wang Zhang, Ziwen Ma, Subhro Das, Lam M Nguyen, and Luca Daniel
                <br>
                <i>Data-driven and Differentiable Simulations, Surrogates, and Solvers Workshop @ NeurIPS 2024</i>
                <br>
                <a href="https://github.com/antbaez/pinn-proj" target="_blank">Code</a>
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              <p>
                <a href="https://aclanthology.org/2023.tsar-1.10.pdf" target="_blank"><b>LSLlama: Fine-tuned LLaMA for Lexical Simplification</b></a>
                <br>
                <b>Anthony Baez</b>, and Horacio Saggion
                <br>
                <i>Second Workshop on Text Simplification, Accessibility and Readability @ EMNLP 2023</i>
                <br>
                <a href="https://github.com/antbaez/LSLlama" target="_blank">Code</a>
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