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
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
Collaborative inference pools distributed resources to run compute-intensive Vision Transformers (ViTs) in satellite edge computing. Model partitioning enables such collaboration by assigning consecutive layer groups to different nodes, but the large volume of intermediate activation data incurs substantial transfer ov...
Yan Chen, Yun-Xiang Zhang, Guan-Jun Jiang et al.· 0 citations
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