Masked language models (MLMs) conventionally mask 15% of tokens due to the belief that
more masking would leave insufficient context to learn good representations; this masking …

Driven by the success of Masked Language Modeling (MLM), the realm of self-supervised
learning for computer vision has been invigorated by the central role of Masked Image …

Parameter-efficient fine-tuning (PEFT) of pre-trained language models has recently
demonstrated remarkable achievements, effectively matching the performance of full fine …

Parameter-efficient fine-tuning (PEFT) of pre-trained language models (PLMs) has emerged
as a highly successful approach, with training only a small number of parameters without …

Memory-efficient finetuning of large language models (LLMs) has recently attracted huge
attention with the increasing size of LLMs, primarily due to the constraints posed by GPU …

Masked Language Modeling (MLM) has been one of the most prominent approaches for
pretraining bidirectional text encoders due to its simplicity and effectiveness. One notable …

Masked Language Models (MLMs) have achieved remarkable success in many self-
supervised representation learning tasks. MLMs are trained by randomly replacing some …

The increasing complexity of agricultural ecosystems and the urgent need for effective plant
health monitoring necessitate advanced technological solutions for processing textual data …