We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base,
Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward. Our models are open
access under the NVIDIA Open Model License Agreement, a permissive model
license that allows distribution, modification, and use of the models and its
outputs. These models perform competitively to open access models on a wide
range of evaluation benchmarks, and were sized to fit on a single DGX H100 with
8 GPUs when deployed in FP8 precision. We believe that the community can
benefit from these models in various research studies and commercial
applications, especially for generating synthetic data to train smaller
language models. Notably, over 98% of data used in our model alignment process
is synthetically generated, showcasing the effectiveness of these models in
generating synthetic data. To further support open research and facilitate
model development, we are also open-sourcing the synthetic data generation
pipeline used in our model alignment process.

我们发布了 Nemotron-4 340B 系列模型，包括 Nemotron-4-340B-Base、Nemotron-4-340B-Instruct 和 Nemotron-4-340B-Reward。这些模型是在 NVIDIA 开放模型许可协议下提供的，允许分发、修改和使用模型及其输出。我们的模型在广泛的评估基准上表现出与开放模型相当的竞争力，并在单个 DGX H100（8 个 GPU）中以 FP8 精度部署。我们相信社区可以在各种研究和商业应用中受益于这些模型，特别是用于生成合成数据以训练较小的语言模型。值得注意的是，我们模型对齐过程中超过 98% 的数据是合成生成的，这显示了这些模型在生成合成数据方面的效果。为了进一步支持开放研究并促进模型开发，我们还开源了在我们的模型对齐过程中使用的合成数据生成流程。

Nemotron-4 340B 技术报告

Nemotron-4 340B Technical Report

In the last few years, several initiatives have been starting to offer access
to research outputs data and metadata in an open fashion. The platforms
developed by those initiatives are opening up scientific production to the
wider public and they can be an invaluable asset for evidence-based
policy-making in Science, Technology and Innovation (STI). These resources can
indeed facilitate knowledge discovery and help identify available R&D assets
and relevant actors within specific research niches of interest. Ideally, to
gain a comprehensive view of entire STI ecosystems, the information provided by
each of these resources should be combined and analysed accordingly. To ensure
so, at least a certain degree of interoperability should be guaranteed across
data sources, so that data could be better aggregated and complemented and that
evidence provided towards policy-making is more complete and reliable. Here, we
study whether this is the case for the case of mapping Climate Action research
in the whole Denmark STI ecosystem, by using 4 popular open access STI data
sources, namely OpenAire, Open Alex, CORDIS and Kohesio.

研究了使用 OpenAire、Open Alex、CORDIS 和 Kohesio 等四个热门开放获取科技创新数据源来绘制整个丹麦 STI 生态系统中的气候行动研究的案例，分析这些资源的互操作性是否得到保障，以便更好地整合和补充数据，并提供更全面可靠的证据支持基于证据的政策制定。

通过开放知识库和人工智能对气候变化研究进行映射：为基于证据的研发政策制定提供的优势和局限性

Mapping Climate Change Research via Open Repositories & AI: advantages and limitations for an evidence-based R&D policy-making

Recent advances in the area of legal information systems have led to a
variety of applications that promise support in processing and accessing legal
documents. Unfortunately, these applications have various limitations, e.g.,
regarding scope or extensibility. Furthermore, we do not observe a trend
towards open access in digital libraries in the legal domain as we observe in
other domains, e.g., economics of computer science. To improve open access in
the legal domain, we present our approach for an open source platform to
transparently process and access Legal Open Data. This enables the sustainable
development of legal applications by offering a single technology stack.
Moreover, the approach facilitates the development and deployment of new
technologies. As proof of concept, we implemented six technologies and
generated metadata for more than 250,000 German laws and court decisions. Thus,
we can provide users of our platform not only access to legal documents, but
also the contained information.

为了改善法律领域的开放性问题，该研究提出了一种透明处理和获取法律开放数据的开源平台，实现了六种技术的应用和超过 25 万条德国法律和法院裁决的元数据生成，提供了对法律文件和其中所包含信息的访问。

法律信息开放平台

Towards an Open Platform for Legal Information

The Durham High Energy Physics Database (HEPData) has been built up over the
past four decades as a unique open-access repository for scattering data from
experimental particle physics papers. It comprises data points underlying
several thousand publications. Over the last two years, the HEPData software
has been completely rewritten using modern computing technologies as an overlay
on the Invenio v3 digital library framework. The software is open source with
the new site available at this https URL now replacing the previous site
at this http URL In this write-up, we describe the development of
the new site and explain some of the advantages it offers over the previous
platform.

Durham High Energy Physics Database (HEPData) has been rebuilt using modern computing technologies, resulting in a new open-access site with advantages over the previous platform, containing a unique repository of scattering data from experimental particle physics papers.