Filling crucial language learning gaps

Inside Praktika's conversational approach to language learning

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

Preserving languages for the future

How Iceland is using GPT-4 to preserve its language.

No Optimal Language Set Exists for Multilingual Instruction Tuning: Insights from a Linguistically-Informed Study

arXiv:2410. 07809v2 Announce Type: replace-cross Abstract: Multilingual instruction tuning (MIT) is challenged by the curse of multilinguality, data scarcity, and high computational cost.

Language models can explain neurons in language models

We use GPT-4 to automatically write explanations for the behavior of neurons in large language models and to score those explanations. We release a dataset of these (imperfect) explanations and scores for every neuron in GPT-2.

GPT-5.3 Instant: Smoother, more useful everyday conversations

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.

Dango: A Strictly L1-Only Large Language Model for Studying Second Language Acquisition

We introduce Dango, a 1. 8B-parameter large language model designed for controlled studies of L1-to-L2 (Japanese-to-English) transfer in second language acquisition (SLA).

Using GPT-4 to improve teaching and learning in Brazil

Improving teaching and learning in Brazil

GPT-4

We’ve created GPT-4, the latest milestone in OpenAI’s effort in scaling up deep learning. GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks.

Efficiently Adapting Spoken Language Models for the Singaporean Context

arXiv:2607. 10092v1 Announce Type: cross Abstract: Spoken language models (SLMs) unify speech perception and reasoning, but adapting them to sensitive domains is underexplored, especially when the original training data is inaccessible and the use case demands multilingual, spoken-query interaction.

Different Perturbations, Different Mechanisms: Understanding Continued Pre-training for Zero-Shot Dialect Robustness

Dialectal variation remains a major challenge for multilingual language models. Perturbation-based continued pre-training (CPT) has emerged as a promising approach to improving robustness, yet existing work largely evaluates individual perturbation strategies in isolation and provides limited insight into why they work.

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

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