—In a federated learning environment with heterogeneous, limited and time-varying computational resource capabilities, it is challenging to update deep neural network in real-time. To address this challenge, we propose FedAD, an adaptive block-dropping approach for federated learning on resource-constrained devices. Fe...
Qi-Qi Cai, Jian Cao, Jian-Qing Zhang et al.· IEEE Transactions on Paralle...· 0 citations
GCA-KBQA is proposed, a step-wise fine-tuned LLM-based framework that employs hop-wise generation, knowledge-assisted calibration, and path-level assembly to construct complete LFs for KBQA, demonstrating its superior performance compared to state-of-the-art baselines.
Ran-Ran Bu, Jian Cao, Jian-Qi Gao et al.· Annual International ACM SIG...· 0 citations
Experiments establish ReTree as an effective self-correcting memory abstraction for long-horizon search, and show that ReTree consistently outperforms Full-Trajectory ReAct in question-answering and search benchmarks.
Aijun Yang, Qianxue Guo, Ziyi Huang et al.· 0 citations
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