3 citations · 3 across the 5 of their papers we have counts for
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cs.AI2025★ 3 cited
MBA-RAG: a Bandit Approach for Adaptive Retrieval-Augmented Generation through Question Complexity
Xiaqiang Tang, Qiang Gao, Jian Li +3
Retrieval Augmented Generation (RAG) has proven to be highly effective in boosting the generative performance of language model in knowledge-intensive tasks. However, existing RAG…
cs.AI2024
Adapting to Non-Stationary Environments: Multi-Armed Bandit Enhanced Retrieval-Augmented Generation on Knowledge Graphs
Xiaqiang Tang, Jian Li, Nan Du +1
Despite the superior performance of Large language models on many NLP tasks, they still face significant limitations in memorizing extensive world knowledge. Recent studies have de…