3 citations · 4 across the 9 of their papers we have counts for
3 papers · 1 filter
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…
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…
Dense Passage Retrieval: Is it Retrieving?
Benjamin Reichman, Larry Heck
Dense passage retrieval (DPR) is the first step in the retrieval augmented generation (RAG) paradigm for improving the performance of large language models (LLM). DPR fine-tunes pr…