AutoHint: Automatic Prompt Optimization with Hint Generation

no code implementations • 13 Jul 2023 • Hong Sun, Xue Li, Yinchuan Xu, Youkow Homma, Qi Cao, Min Wu, Jian Jiao, Denis Charles

This paper presents AutoHint, a novel framework for automatic prompt engineering and optimization for Large Language Models (LLM).

In-Context Learning Prompt Engineering +1

SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance

no code implementations • 30 Aug 2022 • Li Lyna Zhang, Youkow Homma, Yujing Wang, Min Wu, Mao Yang, Ruofei Zhang, Ting Cao, Wei Shen

Remarkably, under our latency requirement of 1900us on CPU, SwiftPruner achieves a 0. 86% higher AUC than the state-of-the-art uniform sparse baseline for BERT-Mini on a large scale real-world dataset.

Extract Dynamic Information To Improve Time Series Modeling: a Case Study with Scientific Workflow

no code implementations • 19 May 2022 • Jeeyung Kim, Mengtian Jin, Youkow Homma, Alex Sim, Wilko Kroeger, Kesheng Wu

In this work, we describe a number of techniques to extract dynamic information about the current state of a large scientific workflow, which could be generalized to other types of applications.

Time Series Time Series Analysis