Heming Xia

Bi-Drop: Enhancing Fine-tuning Generalization via Synchronous sub-net Estimation and Optimization

2023 · arXiv (Cornell University)

Pretrained language models have achieved remarkable success in natural language understanding. However, fine-tuning pretrained models on limited training data tends to overfit and thus diminish performance. This paper presents Bi-Drop, a fine-tuning strategy that selectively …

Enhancing Tool Retrieval with Iterative Feedback from Large Language Models

2024 · arXiv (Cornell University)

Tool learning aims to enhance and expand large language models' (LLMs) capabilities with external tools, which has gained significant attention recently. Current methods have shown that LLMs can effectively handle a certain amount of tools …