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cs.CL2024
Emotional RAG LLMs: Reading Comprehension for the Open Internet
Benjamin Reichman, Adar Avsian, Kartik Talamadupula +2
Queries to large language models (LLMs) can be divided into two parts: the instruction/question and the accompanying context. The context for retrieval-augmented generation (RAG) s…
cs.CL2024★ 1 cited
Are Human Conversations Special? A Large Language Model Perspective
Toshish Jawale, Chaitanya Animesh, Sekhar Vallath +2
This study analyzes changes in the attention mechanisms of large language models (LLMs) when used to understand natural conversations between humans (human-human). We analyze three…