most citedAHP-Powered LLM Reasoning for Multi-Criteria Evaluation of Open-Ended Responses

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cs.CL2025

Emulating Retrieval Augmented Generation via Prompt Engineering for Enhanced Long Context Comprehension in LLMs

Joon Park, Kyohei Atarashi, Koh Takeuchi +1

This paper addresses the challenge of comprehending very long contexts in Large Language Models (LLMs) by proposing a method that emulates Retrieval Augmented Generation (RAG) thro…

cs.CL2024★ 1 cited

AHP-Powered LLM Reasoning for Multi-Criteria Evaluation of Open-Ended Responses

Xiaotian Lu, Jiyi Li, Koh Takeuchi +1

Question answering (QA) tasks have been extensively studied in the field of natural language processing (NLP). Answers to open-ended questions are highly diverse and difficult to q…