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Li-Xu Wang

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#machine learning Preprint Oct 2026

On Unlearning for Time-series Forecasting

Time-series forecasting is widely used in sensitive domains. Models in these settings are often trained on longitudinal user- or entity-level records, which may later require removal because they contain sensitive or proprietary information or have been corrupted by sensor failures. To address such deletion requests wi...

Ze-Yu Shi, Yan-Hui Luo, Zi-Ming Hong et al. · 0 citations
#artificial intelligence Review Oct 2026

Positive-Unlabeled Learning for Agent Safety False Alarm Auditing

Safety monitors help safeguard language-model agents interacting with external tools and environments, but conservative monitoring can generate many false alarms, consuming extensive review resources and weakening trust in alerts. Because false and genuine alarms often remain interleaved in native monitor scores, obtai...

Xi-Chen Yan, Chong-Yang Gao, Ke-Zhen Chen et al. · 0 citations
#machine learning Preprint Sep 2026

Storage Is Not Strategy: State-Conditioned Support Control for LLM Unlearning

Many localized large language model (LLM) unlearning methods select a small parameter subset from a localization signal and keep it fixed during optimization. The parameters most associated with a target, however, need not be the best ones to update, and candidate interventions can change value as optimization proceeds...

Tian-Hao Qian, Zi-Ming Hong, Chong-Yang Gao et al. · 0 citations

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