# Qwenfant: Train Big Character-level BabyLMs on Concise Parallel Text > Source: > Published: 2026-10-15 04:00:00+00:00 # Qwenfant: Train Big Character-level BabyLMs on Concise Parallel Text By Lukas Edman, Alexander FraserSource: [arXiv cs.CL](https://arxiv.org/list/cs.CL/recent) arXiv:2610.19294v1 Announce Type: new Abstract: This work concerns our submission for the Multilingual track of the 2026 BabyLM Challenge. We improve on our baseline using data that has been summarized and translated by an [LLM](https://www.machinebrief.com/glossary/llm), showing that higher-quality data can come from synthetic sources. We further improve with 2 simple changes: using a larger model, and using a character-level vocabulary. Both of these changes require[LoRA](https://www.machinebrief.com/glossary/lora)-style[fine-tuning](https://www.machinebrief.com/glossary/fine-tuning)for realizing their full potential. We dub our final Qwen3-based model Qwenfant, which, at the time of submission, ranks 1st in the Multilingual track. Get AI news in your inbox Daily digest of what matters in AI.