Author

Feifei Zhang

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Preprint Jul 2026

Self-Improving is Often Sudden: Enlightenment-style Finetuning for Large-Scale Models

The pursuit of autonomously self-improving models has attracted growing interest in the era of large-scale foundation models. Drawing inspiration from the concept of"enlightenment"or"aha moment"in human brain, we hypothesize that large models exhibit an analogous enlightenment phenomenon-a latent capacity for sudden ca...

Jingxiao Liao, Tianwei Zhang, Yu-Hao Jiang et al. · 0 citations

Preprint Jul 2026

Hidden Decoding at Scale: Latent Computation Scaling for Large Language Models

Scaling Large Language Models (LLMs) has been driven mainly by enlarging the Transformer backbone, but for an already-strong model this requires another round of costly pretraining. We study whether an existing backbone can keep improving by allocating more computation to each token while leaving the Transformer backbo...

Aiwei Liu, Cheng Shi, Chuhan Wu et al. · 2 citations