Search Results for author:
Found 4 papers, 3 papers with code
Adapting Large Language Models via Reading Comprehension
Taken inspiration from human learning via reading comprehension--practice after reading improves the ability to answer questions based on the learned knowledge--we propose a simple method for transforming raw corpora into reading comprehension texts.
How Does Diffusion Influence Pretrained Language Models on Out-of-Distribution Data?
It shows that finetuning PLMs with diffusion degrades the reconstruction ability on OOD data.
UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation
Large Language Models (LLMs) are popular for their impressive abilities, but the need for model-specific fine-tuning or task-specific prompt engineering can hinder their generalization.
VL-Match: Enhancing Vision-Language Pretraining with Token-Level and Instance-Level Matching
Vision-Language Pretraining (VLP) has significantly improved the performance of various vision-language tasks with the matching of images and texts.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
