Fedus, William

Scaling Instruction-Finetuned Language Models

Chung, H. W., Hou, L., Longpre, S., Zoph, B., Tay, Y., Fedus, W., Li, Y., Wang, X., Dehghani, M., Brahma, S., et al. (2022) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 1,441

Emergent Abilities of Large Language Models

Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,264

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

Fedus, W., Zoph, B., & Shazeer, N. (2021) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 1,005

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images

Christiansen, E. M., Yang, S. J., Ando, D. M., Javaherian, A., Skibinski, G., Lipnick, S., Mount, E., O’Neil, A., Shah, K., Lee, A. K., et al. (2018) · Cell

Cell Image Analysis TechniquesAdvanced Fluorescence Microscopy Techniques

Cited by 635

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

A Review of Sparse Expert Models in Deep Learning

Fedus, W., Dean, J., & Zoph, B. (2022) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 196

Language GANs Falling Short

Caccia, M., Caccia, L., Fedus, W., Larochelle, H., Pineau, J., & Charlin, L. (2018) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 83

Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers

Tay, Y., Dehghani, M., Rao, J., Fedus, W., Abnar, S., Chung, H. W., Narang, S., Yogatama, D., Vaswani, A., & Metzler, D. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 63

Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?

Tay, Y., Dehghani, M., Abnar, S., Chung, H., Fedus, W., Rao, J., Narang, S., Tran, V., Yogatama, D., & Metzler, D. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023

Topic ModelingNatural Language Processing Techniques

Cited by 34

Measuring short-form factuality in large language models

Wei, J., Karina, N., Chung, H. W., Jiao, Y. J., Papay, S., Glaese, A., Schulman, J., & Fedus, W. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 14

Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?

Tay, Y., Dehghani, M., Abnar, S., Chung, H. W., Fedus, W., Rao, J., Narang, S., Tran, V. Q., Yogatama, D., & Metzler, D. (2022) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 11

BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents

Wei, J., Sun, Z., Papay, S., McKinney, S., Han, J., Fulford, I., Chung, H. W., Passos, A. T., Fedus, W., & Glaese, A. (2025) · arXiv

Information Retrieval and Search BehaviorWeb Data Mining and Analysis

Cited by 2