163 citations · 200 across the 13 of their papers we have counts for
3 papers · 1 filter
Phi-4 Technical Report
Marah Abdin, Jyoti Aneja, Harkirat Behl +24
We present phi-4, a 14-billion parameter language model developed with a training recipe that is centrally focused on data quality. Unlike most language models, where pre-training…
On the Diversity of Synthetic Data and its Impact on Training Large Language Models
Hao Chen, Abdul Waheed, Xiang Li +4
The rise of Large Language Models (LLMs) has accentuated the need for diverse, high-quality pre-training data. Synthetic data emerges as a viable solution to the challenges of data…
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…