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cs.LG2024
LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers
Xuan Shen, Zhao Song, Yufa Zhou +12
Diffusion Transformers have emerged as the preeminent models for a wide array of generative tasks, demonstrating superior performance and efficacy across various applications. The…
cs.AI2024
Unified Parameter-Efficient Unlearning for LLMs
Chenlu Ding, Jiancan Wu, Yancheng Yuan +5
The advent of Large Language Models (LLMs) has revolutionized natural language processing, enabling advanced understanding and reasoning capabilities across a variety of tasks. Fin…
cs.CL2024★ 1 cited
SoftDedup: an Efficient Data Reweighting Method for Speeding Up Language Model Pre-training
Nan He, Weichen Xiong, Hanwen Liu +6
The effectiveness of large language models (LLMs) is often hindered by duplicated data in their extensive pre-training datasets. Current approaches primarily focus on detecting and…