Few-shot class-incremental learning (FSCIL) requires a model to absorb new visual classes from a handful of labeled examples while preserving decisions for previously seen classes. Prototype insertion is attractive because it avoids incremental optimization, yet a single embedding geometry can make few-shot prototypes...
Jibing Wu, Z. Mao, Hang Zhang et al.· 2026 12th International Conf...· 0 citations
Non-stationary data streams suffer from simultaneous data and concept drifts that degrade model generalization. Conventional Automated Machine Learning for data streams, AML4S, relies on single-pipeline architecture with univariate ADWIN detection and exhaustive post-drift reconstruction, causing knowledge waste and in...
Jia-Qiang Zhang, Hang Zhang, Ning-Chao Ge et al.· 2026 12th International Conf...· 0 citations
Large language models (LLMs) have rapidly advanced natural-language-to-query (Text-to-Query) capabilities, yet existing public benchmarks remain confined to single database paradigms such as Text-to-SQL or Text-to-KG. They do not capture real-world settings where relational databases, graph databases, document database...
Guo-Shen Li, Hang Zhang, Ying-Jun Liu et al.· 2026 12th International Conf...· 0 citations
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