Author

Bo-Han Jiang

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#artificial intelligence Preprint Sep 2026

Active Budget Can Kill Sensitivity: Diagnosing and Repairing TopK Sparse Autoencoder Reliability

The results suggest that wide TopK SAEs should be evaluated not only by reconstruction, sparsity, and feature count, but also by feature reliability under semantic variation and boundary geometry for stable interpretability.

Zhen-Ting Huang, Bo-Han Jiang, J. Liu et al. · 0 citations

#machine learning Preprint Aug 2026

Predicting the Unpredictable: LLM-powered Long-term Chaotic Time Series Forecasting under Short-term Observations

PAC-LLM is proposed, a phase-space-aware adaptive fusion framework for long-term chaotic time series forecasting powered by LLMs that leverages learned phase-space features and textual information to fully enable LLM's time series forecasting capacity.

Yue Yao, Bo-Han Jiang · 0 citations