Author

Hua-Xing Liu

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Preprint Aug 2026

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning

J-Access is proposed, an inference-time audit that uses the Jacobian lens to map intermediate representations into vocabulary space and measures how often target concepts remain accessible along the model's output pathway, positioning J-Access as a model-level diagnostic for assessing residual susceptibility in unlearn...

Zirui Song, Hua-Xing Liu, Xiang Wang et al. · 1 citation

Jul 2026

Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias

Existing studies of LLM-as-judge scoring bias work predominantly at the input-output level: they perturb inputs, measure score deltas, and propose prompt-level mitigations. We argue that the same biases admit a representation-level account in the judge's hidden state, complementary to the input-output view and operatio...

Zixiang Xu, Sixian Li, Hua-Xing Liu et al. · arXiv.org · 2 citations