Multi-dimensional data refining strategy for effective fine-tuning LLMs

no code implementations • 2 Nov 2023 • Thanh Nguyen Ngoc, Quang Nhat Tran, Arthur Tang, Bao Nguyen, Thuy Nguyen, Thanh Pham

Data is a cornerstone for fine-tuning large language models, yet acquiring suitable data remains challenging.

Vietnamese Language Models

AI-assisted Learning for Electronic Engineering Courses in High Education

no code implementations • 2 Nov 2023 • Thanh Nguyen Ngoc, Quang Nhat Tran, Arthur Tang, Bao Nguyen, Thuy Nguyen, Thanh Pham

This study evaluates the efficacy of ChatGPT as an AI teaching and learning support tool in an integrated circuit systems course at a higher education institution in an Asian country.

Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark

no code implementations • 29 Mar 2021 • Sharada Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Gražvydas Šemetulskis, João Schapke, Jonas Kubilius, Jurgis Pašukonis, Linas Klimas, Matthew Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe

We present the design of a centralized benchmark for Reinforcement Learning which can help measure Sample Efficiency and Generalization in Reinforcement Learning by doing end to end evaluation of the training and rollout phases of thousands of user submitted code bases in a scalable way.

reinforcement-learning Reinforcement Learning (RL)