Jun, Heewoo

Evaluating Large Language Models Trained on Code

Chen, M., Tworek, J., Jun, H., Yuan, Q., Pinto, H. P. D. O., Kaplan, J., Edwards, H., Burda, Y., Joseph, N., Brockman, G., et al. (2021) · arXiv

Software Engineering ResearchNatural Language Processing Techniques

Cited by 1,436

Deep Learning Scaling is Predictable, Empirically

Hestness, J., Narang, S., Ardalani, N., Diamos, G., Jun, H., Kianinejad, H., Patwary, M. M. A., Yang, Y., & Zhou, Y. (2017) · arXiv

Machine Learning and Data ClassificationStochastic Gradient Optimization Techniques

Cited by 427

GPT-4o System Card

OpenAI, :, Hurst, A., Lerer, A., Goucher, A. P., Perelman, A., Ramesh, A., Clark, A., Ostrow, A., Welihinda, A., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 180

Scaling Laws for Autoregressive Generative Modeling

Henighan, T., Kaplan, J., Katz, M., Chen, M., Hesse, C., Jackson, J., Jun, H., Brown, T. B., Dhariwal, P., Gray, S., et al. (2020) · arXiv

Advanced Neural Network ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 150

Efficient Training of Language Models to Fill in the Middle

Bavarian, M., Jun, H., Tezak, N., Schulman, J., McLeavey, C., Tworek, J., & Chen, M. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 47