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NCP-ArchPreview model advances language modeling with concept prediction

By PulseAugur Editorial · [6 sources] ·

Researchers have introduced NCP-ArchPreview, a novel latent-space language model that moves beyond traditional next-token prediction. This model incorporates Next Concept Prediction (NCP), enabling it to learn and predict discrete concepts that span multiple tokens. Trained on 5.73T tokens from the Dolma-3 dataset, the 8.9B parameter model achieved the pretraining loss of OLMo-3-7B using only 51.3% of the training tokens and demonstrated significant gains on downstream tasks, including a 5.99-point improvement on GSM8K. AI

IMPACT This new approach to language modeling could lead to more efficient training and improved performance on complex reasoning tasks.

RANK_REASON The cluster describes a technical report detailing a new language model architecture and its performance, fitting the research bucket.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 6 sources. How we write summaries →

NCP-ArchPreview model advances language modeling with concept prediction

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COVERAGE [6]

  1. arXiv cs.CL TIER_1 English(EN) · NCP Team, Jiaqi Cao, Chiyu Chen, Shuang Cheng, Xu Cheng, Beiya Dai, Yufan Feng, Kewen Ge, Ruijun Ge, Jiayi Huang, Yang Jiao, Dahua Lin, Zhouhan Lin, Yifan Liu, Yuliang Liu, Biqing Qi, Mowen Ruan, Junzhe Shen, Yunchong Song, Hao Sun, Zhongbo Tian, Yixuan … ·

    NCP-ArchPreview Technical Report: Moving towards Latent Space Language Models through Next Concept Prediction

    arXiv:2609.10715v1 Announce Type: new Abstract: We introduce NCP-ArchPreview, a latent-space language model that pushes autoregressive pretraining beyond standard next-token prediction (NTP). Alongside NTP, the model learns through Next Concept Prediction (NCP) to predict discret…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    NCP-ArchPreview Technical Report: Moving towards Latent Space Language Models through Next Concept Prediction

    NCP-ArchPreview is a large latent-space language model that jointly trains next-token and next-concept prediction to improve pretraining efficiency and downstream performance.

  3. Pandaily TIER_1 English(EN) · [email protected] (Pandaily) ·

    Shanghai AI Lab and SJTU Open-Source NCP-ArchPreview Latent-Space Model

    Shanghai Artificial Intelligence Laboratory and Shanghai Jiao Tong University's LUMIA Lab open-sourced NCP-ArchPreview, an 8.9B latent-space model that jointly trains next-concept and next-token prediction, matching a 7B baseline loss on ~51.3% of tokens.

  4. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    Shanghai AI Lab and SJTU have open-sourced NCP-ArchPreview, an 8.9B parameter latent-space language model. The model jointly trains next-concept and next-token

    Shanghai AI Lab and SJTU have open-sourced NCP-ArchPreview, an 8.9B parameter latent-space language model. The model jointly trains next-concept and next-token prediction, achieving a 7B baseline loss using just 51.3% of the training tokens. This marks the largest demonstration o…

    LINKS pandaily.com/shanghai-ai-lab-sjtu-ncp-arc…
  5. Mastodon — mastodon.social TIER_1 English(EN) · opensourceaitech ·

    📄 Paper «NCP-ArchPreview» shifts language modeling from next token to next concept prediction in latent space. 177 upvotes on HF suggest strong interest. https:

    📄 Paper «NCP-ArchPreview» shifts language modeling from next token to next concept prediction in latent space. 177 upvotes on HF suggest strong interest. https:// huggingface.co/papers/2609.107 15 # AI # MachineLearning # Research

    LINKS huggingface.co/…/2609.10715
  6. Mastodon — mastodon.social TIER_1 English(EN) · opensourceaitech ·

    📄 'NCP-ArchPreview Technical Report' moves from token prediction to next concept prediction in latent space. With 22 upvotes on Hugging Face, this approach reth

    📄 'NCP-ArchPreview Technical Report' moves from token prediction to next concept prediction in latent space. With 22 upvotes on Hugging Face, this approach rethinks language model reasoning. Read the report: https:// huggingface.co/papers/2609.107 15 # AI # MachineLearning # Rese…

    LINKS huggingface.co/…/2609.10715

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