Author

Fu-Gen Yao

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#artificial intelligence Preprint Sep 2026

COPE: Continual Personalization of LLMs under Sparse User Feedback via User Embeddings and Self-Evaluation

Experiments show that COPE consistently outperforms strong training-free and training-based baselines under sparse feedback, and remains complementary to Retrieval-Augmented Prompting, and further analyses confirm COPE's reliable self-evaluation, meaningful preference patterns, stable general capabilities, and robustne...

Rui-Ke Cao, Fu-Gen Yao, Liang Dong et al. · 0 citations

#artificial intelligence Preprint Sep 2026

RPMem: Learning Long-Term Recurrent Parametric Memory Across Sessions for LLM Agents

Long-running LLM agents require memory that persists and evolves across sessions. Text-based memory retrieves and reconstructs past interactions at every query, making long-horizon performance increasingly dependent on retrieval quality and contextual reasoning as histories grow. Parametric memory encodes experience di...

Fan-Yu Zhao, Rui-Ke Cao, Liang Dong et al. · 0 citations

#artificial intelligence Preprint Sep 2026

MemCalib: Benchmarking and Optimizing Memory Use in LLM Agents

MemCalib-RL is proposed, an ordered bidirectional counterfactual credit-assignment algorithm that separates over- and under-use signals and localizes their credit to response tokens through exact atom ablation and achieves the best overall performance while better balancing over-use and under-use.

Rui-Ke Cao, Fan-Yu Zhao, Fu-Gen Yao et al. · 0 citations