3 papers
cs.CL2024
Automatic Instruction Evolving for Large Language Models
Weihao Zeng, Can Xu, Yingxiu Zhao +2
Fine-tuning large pre-trained language models with Evol-Instruct has achieved encouraging results across a wide range of tasks. However, designing effective evolving methods for in…
cs.CL2024
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Marah Abdin, Jyoti Aneja, Hany Awadalla +126
We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal test…
cs.CL2023
Learning From Mistakes Makes LLM Better Reasoner
Shengnan An, Zexiong Ma, Zeqi Lin +3
Large language models (LLMs) recently exhibited remarkable reasoning capabilities on solving math problems. To further improve their reasoning capabilities, this work explores whet…