2.3k citations · 3.9k across the 6 of their papers we have counts for
6 papers
OpenAI o1 System Card
OpenAI, :, Aaron Jaech +261
The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. These advanced reasoning capabilities provide new avenues for improving the…
Evaluating Large Language Models Trained on Code
Mark Chen, Jerry Tworek, Heewoo Jun +55
We introduce Codex, a GPT language model fine-tuned on publicly available code from GitHub, and study its Python code-writing capabilities. A distinct production version of Codex p…
Extensions and Limitations of the Neural GPU
Eric Price, Wojciech Zaremba, Ilya Sutskever
The Neural GPU is a recent model that can learn algorithms such as multi-digit binary addition and binary multiplication in a way that generalizes to inputs of arbitrary length. We…
Addressing the Rare Word Problem in Neural Machine Translation
Minh-Thang Luong, Ilya Sutskever, Quoc V. Le +2
Neural Machine Translation (NMT) is a new approach to machine translation that has shown promising results that are comparable to traditional approaches. A significant weakness in…
Recurrent Neural Network Regularization
Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals
We present a simple regularization technique for Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) units. Dropout, the most successful technique for regularizing…
Learning to Discover Efficient Mathematical Identities
Wojciech Zaremba, Karol Kurach, Rob Fergus
In this paper we explore how machine learning techniques can be applied to the discovery of efficient mathematical identities. We introduce an attribute grammar framework for repre…