13 citations · 15 across the 10 of their papers we have counts for
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cs.IR2024
No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users
Mengxuan Hu, Hongyi Wu, Zihan Guan +4
Retrieval-Augmented Generation (RAG) is widely adopted for its effectiveness and cost-efficiency in mitigating hallucinations and enhancing the domain-specific generation capabilit…
cs.CV2024
Reminding Multimodal Large Language Models of Object-aware Knowledge with Retrieved Tags
Daiqing Qi, Handong Zhao, Zijun Wei +1
Despite recent advances in the general visual instruction-following ability of Multimodal Large Language Models (MLLMs), they still struggle with critical problems when required to…