Preserving languages for the future

Filling crucial language learning gaps

GPT-4 deepens the conversation on Duolingo.

GPTs are GPTs: An early look at the labor market impact potential of large language models

Inside Praktika's conversational approach to language learning

How Praktika uses GPT-4. 1 and GPT-5.

Introducing OpenAI Japan

We are excited to announce our first office in Asia and we’re releasing a GPT-4 custom model optimized for the Japanese language.

GPT-2: 1.5B release

As the final model release of GPT-2’s staged release, we’re releasing the largest version (1. 5B parameters) of GPT-2 along with code and model weights to facilitate detection of outputs of GPT-2 models.

Minnesota’s Enterprise Translation Office uses ChatGPT to bridge language gaps

Minnesota’s Enterprise Translation Office uses ChatGPT to bridge language gaps

GPT-2: 6-month follow-up

We’re releasing the 774 million parameter GPT-2 language model after the release of our small 124M model in February, staged release of our medium 355M model in May, and subsequent research with partners and the AI community into the model’s potential for misuse and societal benefit. We’re also releasing an open-source legal agreement to make it easier for organizations to initiate model-sharing partnerships with each other, and are publishing a technical report about our experience in coordinating with the wider AI research community on publication norms.

CoPiT: Cognitive Pivot Translation for Digraphic Low-Resource Mongolian in the Traditional Script

Low-resource languages remain challenging for machine translation, and Mongolian is a representative case. As a digraphic language, Mongolian is written in both Cyrillic and Traditional scripts, which exhibit a severe imbalance in data availability.

Making education data accessible

Zelma uses GPT-4 to make education data accessible.

TabletCraft: Bridging a 4,000-Year Cultural Gap with Bidirectional Akkadian NMT and Cuneiform Rendering

arXiv:2608. 02609v1 Announce Type: cross Abstract: Half a million cuneiform clay tablets survive in museums worldwide, yet modern users can neither read nor write in the world's oldest writing system, leaving a 4,000-year cultural barrier that existing NLP tools have only partially addressed.

LuxInstruct: A Cross-Lingual Instruction Tuning Dataset For Luxembourgish

arXiv:2510. 07074v2 Announce Type: replace-cross Abstract: Instruction tuning has become a key technique for enhancing the performance of large language models, enabling them to better follow human prompts.

Cross-Lingual Transfer for Machine Translation in Turkic Languages

arXiv:2607. 29355v1 Announce Type: cross Abstract: Cross-lingual transfer is central to low-resource machine translation, but its behavior within closely related language families remains insufficiently characterized.