6 citations · 11 across the 6 of their papers we have counts for
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cs.CL2024
IM-RAG: Multi-Round Retrieval-Augmented Generation Through Learning Inner Monologues
Diji Yang, Jinmeng Rao, Kezhen Chen +4
Although the Retrieval-Augmented Generation (RAG) paradigms can use external knowledge to enhance and ground the outputs of Large Language Models (LLMs) to mitigate generative hall…
cs.CL2024★ 4 cited
Higher Layers Need More LoRA Experts
Chongyang Gao, Kezhen Chen, Jinmeng Rao +7
Parameter-efficient tuning (PEFT) techniques like low-rank adaptation (LoRA) offer training efficiency on Large Language Models, but their impact on model performance remains limit…
cs.CL2023★ 1 cited
Tackling Vision Language Tasks Through Learning Inner Monologues
Diji Yang, Kezhen Chen, Jinmeng Rao +4
Visual language tasks require AI models to comprehend and reason with both visual and textual content. Driven by the power of Large Language Models (LLMs), two prominent methods ha…