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October 20, 2025Open Access

TRACE: Training and Inference-Time Interpretability Analysis for Language Models

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Modular toolkit enhances interpretability of transformer models during training, suggesting insights into linguistic feature acquisition.

TRACE reveals early syntactic emergence and delayed semantic acquisition in language models, enhancing interpretability.
The toolkit enables analysis of linguistic signals using features probing and Hessian curvature, making it efficient.
Using TRACE with autoregressive transformers shows it captures developmental phenomena missed by traditional metrics.
The tool promotes actionable insights and reproducibility with layer-wise diagnostics and convergence-based early stopping.

Aljaafari et al. (2025) studied this question.

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October 20, 2025Open Access

View Full Paper

Ask AI

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Authors

Modular toolkit enhances interpretability of transformer models during training, suggesting insights into linguistic feature acquisition.

TRACE reveals early syntactic emergence and delayed semantic acquisition in language models, enhancing interpretability.
The toolkit enables analysis of linguistic signals using features probing and Hessian curvature, making it efficient.
Using TRACE with autoregressive transformers shows it captures developmental phenomena missed by traditional metrics.
The tool promotes actionable insights and reproducibility with layer-wise diagnostics and convergence-based early stopping.

Aljaafari et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark