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

Transformer models have demonstrated remarkable performance in neural machine
translation (NMT). However, their vulnerability to noisy input poses a significant challenge in …

Encoder-decoder architecture is widely adopted for sequence-to-sequence modeling tasks.
For machine translation, despite the evolution from long short-term memory networks to …

Mutual learning, where multiple agents learn collaboratively and teach one another, has
been shown to be an effective way to distill knowledge for image classification tasks. In this …

The field of statistical language modeling and machine translation has seen rapid
developments in recent years, with artificial neural networks taking center of the stage …