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cs.CL2024★ 1 cited
TransformLLM: Adapting Large Language Models via LLM-Transformed Reading Comprehension Text
Iftach Arbel, Yehonathan Refael, Ofir Lindenbaum
Large Language Models (LLMs) have shown promise in highly-specialized domains, however challenges are still present in aspects of accuracy and costs. These limitations restrict the…
cs.CL2024
Knowledge Editing in Language Models via Adapted Direct Preference Optimization
Amit Rozner, Barak Battash, Lior Wolf +1
Large Language Models (LLMs) can become outdated over time as they may lack updated world knowledge, leading to factual knowledge errors and gaps. Knowledge Editing (KE) aims to ov…