context2 [논문] RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective AugmentationRetrieving documents and prepending them in-context at inference time improves performance of language model (LMs) on a wide range of tasks. However, these documents, often spanning hundreds of words, make inference substantially more expensive. We proposearxiv.orgAbstractRetrieving documents and prepending them.. 2025. 1. 9. [논문] Compressing Context to Enhance Inference Efficiency of Large Language Models Compressing Context to Enhance Inference Efficiency of Large Language ModelsYucheng Li, Bo Dong, Frank Guerin, Chenghua Lin. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. 2023.aclanthology.orgAbstractLarge language models (LLMs) achieved remarkable performance across various tasks. However, they face challenges in managing long documents and extended con.. 2025. 1. 9. 이전 1 다음 반응형
