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cs.CL2026
Can LLMs Be Constrained to the Past? Improving Knowledge Cutoff through Recall-Based Prompting
Michiro Asai, Ailiang Lin, Yu Kishimoto +4
Prompted knowledge cutoff instructs a large language model (LLM) to act as if information beyond a specified cutoff date were unavailable. However, prior work mainly relies on dire…
cs.CL2024
DiLM: Distilling Dataset into Language Model for Text-level Dataset Distillation
Aru Maekawa, Satoshi Kosugi, Kotaro Funakoshi +1
Dataset distillation aims to compress a training dataset by creating a small number of informative synthetic samples such that neural networks trained on them perform as well as th…