Child, Rewon

Language Models are Few-Shot Learners

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 23,372

Scaling Laws for Neural Language Models

Kaplan, J., McCandlish, S., Henighan, T., Brown, T. B., Chess, B., Child, R., Gray, S., Radford, A., Wu, J., & Amodei, D. (2020) · arXiv

Artificial Intelligence ApplicationsTopic Modeling

Cited by 9,550

PaLM: Scaling Language Modeling with Pathways

Chowdhery, A., Narang, S., Devlin, J., Bosma, M., Mishra, G., Roberts, A., Barham, P., Chung, H. W., Sutton, C., Gehrmann, S., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2,590

Generating Long Sequences with Sparse Transformers

Child, R., Gray, S., Radford, A., & Sutskever, I. (2019) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 1,063

Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model

Smith, S., Patwary, M., Norick, B., LeGresley, P., Rajbhandari, S., Casper, J., Liu, Z., Prabhumoye, S., Zerveas, G., Korthikanti, V., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 286

Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images

Child, R. (2020) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 140