Search Results for author:
Found 3 papers, 0 papers with code
Look Before You Leap: Towards Decision-Aware and Generalizable Tool-Usage for Large Language Models
Meanwhile, we propose a novel tool sampling strategy to enhance the generalizability of LLMs over unseen tools.
G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks
However, with the growth of model scale and the rising number of downstream tasks, this paradigm inevitably meets the challenges in terms of computation consumption and memory footprint issues.
HiFi: High-Information Attention Heads Hold for Parameter-Efficient Model Adaptation
To fully leverage the advantages of large-scale pre-trained language models (PLMs) on downstream tasks, it has become a ubiquitous adaptation paradigm to fine-tune the entire parameters of PLMs.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
