English(EN) Dory1.0-4B: A Looped Normalized-GPT

Nemotron Labs发布Dory1.0-4B循环语言模型

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 00:00

Nemotron Labs发布了Dory1.0-4B，一个拥有40亿参数的语言模型，它采用了新颖的循环架构。该设计通过多次应用共享层块，有效地用推理计算换取更好的性能，从而提高了模型的准确性和令牌效率。Dory1.0-4B在各种基准测试中，尤其是在编码和智能体任务上，表现优于更大的模型，并且其检查点现已公开可用。 AI

影响引入了一种新颖的循环架构，提高了效率和性能，可能影响未来的LLM设计。

排序理由前沿实验室模型发布，附带系统卡。[lever_c_从frontier_release降级：ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Significant; 前沿实验室模型发布，附带系统卡。[lever_c_从frontier_release降级：ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: model release, paper; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: 8 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

Hugging Face Daily Papers TIER_1 English(EN) · 2026-11-02 00:00

Dory1.0-4B：一个循环归一化GPT

Dory1.0-4B is a 4-billion-parameter recurrent language model with elastic depth that improves accuracy and token efficiency by looping a shared block, outperforming larger models on multiple benchmarks.

本文如何被排名

报道来源 [1]

Dory1.0-4B：一个循环归一化GPT

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