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Found 5 papers, 3 papers with code
Generalizable and Stable Finetuning of Pretrained Language Models on Low-Resource Texts
Pretrained Language Models (PLMs) have advanced Natural Language Processing (NLP) tasks significantly, but finetuning PLMs on low-resource datasets poses significant challenges such as instability and overfitting.
AutoLoRA: Automatically Tuning Matrix Ranks in Low-Rank Adaptation Based on Meta Learning
Large-scale pretraining followed by task-specific finetuning has achieved great success in various NLP tasks.
Downstream Task Guided Masking Learning in Masked Autoencoders Using Multi-Level Optimization
Masked Autoencoder (MAE) is a notable method for self-supervised pretraining in visual representation learning.
Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models
Large language models generate high-quality responses with potential misinformation, underscoring the need for regulation by distinguishing AI-generated and human-written texts.
Improving Differentiable Architecture Search with a Generative Model
We introduce a training strategy called ``Differentiable Architecture Search with a Generative Model(DASGM)."
