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Cheng-Xi Li

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Preprint Aug 2026

Puro-2B: Poor Lab's Qwen2-1.5B Trained on RTX 5090 within $5090

This report presents an open pretraining recipe that trains a collection of Puro-2B models from scratch on up to 1.4 trillion tokens with FP8 precision on consumer-grade RTX 5090 GPUs, and derives a Puro Cost Scaling Law that relates training cost to average model performance.

Kai-Rong Luo, Jia-Rui Cui, Yao-Rui Yin et al. · 1 citation
#natural language process... Conference Apr 2025

Efficient and Adaptive Simultaneous Speech Translation with Fully Unidirectional Architecture

Experiments on both in-domain (MuST-C) and out-of-domain (Europarl-ST) En-De and En-Es datasets demonstrate that EASiST offers superior latency-quality trade-offs compared to several strong baselines.

Biao Fu, Donglei Yu, Min-Peng Liao et al. · 16 citations · ⚡1

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