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cs.CL2025★ 1 cited
All for law and law for all: Adaptive RAG Pipeline for Legal Research
Figarri Keisha, Prince Singh, Pallavi +5
Retrieval-Augmented Generation (RAG) has transformed how we approach text generation tasks by grounding Large Language Model (LLM) outputs in retrieved knowledge. This capability i…
cs.CL2023
Walking a Tightrope -- Evaluating Large Language Models in High-Risk Domains
Chia-Chien Hung, Wiem Ben Rim, Lindsay Frost +2
High-risk domains pose unique challenges that require language models to provide accurate and safe responses. Despite the great success of large language models (LLMs), such as Cha…