ModelScope(@ModelScope2022):Shanghai AI Lab and SJTU’s LUMIA Lab release NCP-ArchPreview, an open-weight 8.9B language modell. 📜 Apache 2.0. 🤖 https://t.co/6AbJmQXRh7 📄 https://t.co/Hph9G7ZmTw ⚡ Trained on 5.73T Dolma 3 tokens, it reaches OLMo-3-7B’s final Stage 1 loss with only 51.3% of the tokens, a 1.95× convergence gain. 🏆 Its Stage 1 macro-average rises from 46.59 to 49.04, with +5.99 on GSM8K and +4.28 on HumanEval. 🧠 NCP jointly predicts tokens and a concept sequence at one-quarter the length, then feeds those concepts back to guide generation. 🛠 Domain adaptation updates only the 17M-parameter concept module while keeping the token backbone frozen. 🚀 Concept-conditioned drafting improves mean accepted length by 4.17% with negligible overhead.

ModelScope@ModelScope2022

2026.09.23 05:00

Shanghai AI Lab and SJTU’s LUMIA Lab release NCP-ArchPreview, an open-weight 8.9B language modell. 📜 Apache 2.0. 🤖 📄 ⚡ Trained on 5.73T Dolma 3 tokens, it reaches OLMo-3-7B’s final Stage 1 loss with only 51.3% of the tokens, a 1.95× convergence gain. 🏆 Its Stage 1 macro-average rises from 46.59 to 49.04, with +5.99 on GSM8K and +4.28 on HumanEval. 🧠 NCP jointly predicts tokens and a concept sequence at one-quarter the length, then feeds those concepts back to guide generation. 🛠 Domain adaptation updates only the 17M-parameter concept module while keeping the token backbone frozen. 🚀 Concept-conditioned drafting improves mean accepted length by 4.17% with negligible overhead.