Le Hou

Traditional Library's Service Mode Transformation Based on Resources Relocation

2015 · Sci-Tech Information Development & Economy

This paper introduces the concept and component elements of library resources,probes into some details of traditional library's service mode transformation based on resources relocation,sums up some experiences of traditional library's service mode transformation,and points out …

Unsupervised Histopathology Image Synthesis

2017 · arXiv (Cornell University)

Hematoxylin and Eosin stained histopathology image analysis is essential for the diagnosis and study of complicated diseases such as cancer. Existing state-of-the-art approaches demand extensive amount of supervised training data from trained pathologists. In this …

Symbol tuning improves in-context learning in language models

2023 · arXiv (Cornell University)

We present symbol tuning - finetuning language models on in-context input-label pairs where natural language labels (e.g., "positive/negative sentiment") are replaced with arbitrary symbols (e.g., "foo/bar"). Symbol tuning leverages the intuition that when a model …

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

2022 · arXiv (Cornell University)

Chain-of-thought prompting has demonstrated remarkable performance on various natural language reasoning tasks. However, it tends to perform poorly on tasks which requires solving problems harder than the exemplars shown in the prompts. To overcome this …

Scaling Instruction-Finetuned Language Models

2022 · arXiv (Cornell University)

Finetuning language models on a collection of datasets phrased as instructions has been shown to improve model performance and generalization to unseen tasks. In this paper we explore instruction finetuning with a particular focus on …