Update README.md

README.md

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 # Synthetic data seeds/environment
 
 We provide synthetic datasets and environments grounded in open or licenced proprietary seed material, the specifications and the pipelines needed to generate at scale. Each environment is anchored in a real structured asset such demographic distributions, knowledge graphs, etc. 
-Our NeurIPS 2026 paper measures what this is worth. SYNTH — ~80B tokens generated from 58,000 seed articles — trains models that sit on the token-efficiency frontier with no SFT or RL stage at all: within 0.7 points of Qwen3-0.6B on open-ended tasks at 80–700× fewer training tokens, and best-in-tier factual precision at 10–140× fewer tokens.
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+Our synthetic pretraining paper currently under submission to Neurips provides a wider assement of our generalist synthetic pipelines. <a href="https://huggingface.co/datasets/PleIAs/SYNTH>SYNTH</a> (~80B tokens generated from 58,000 seed articles) trains models that sit on the token-efficiency frontier with no SFT or RL stage at all: within 0.7 points of Qwen3-0.6B on open-ended tasks at 80–700× fewer training tokens, and best-in-tier factual precision at 10–140× fewer tokens.
 
 ## Global personas.