Tay, Yi

DSI++: Updating Transformer Memory with New Documents

Mehta, S., Gupta, J., Tay, Y., Dehghani, M., Tran, V., Rao, J., Najork, M., Strubell, E., & Metzler, D. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Topic ModelingInformation Retrieval and Search Behavior

Cited by 21

BIG-Bench Extra Hard

Kazemi, M., Fatemi, B., Bansal, H., Palowitch, J., Anastasiou, C., Mehta, S. V., Jain, L. K., Aglietti, V., Jindal, D., Chen, P., et al. (2025) · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 15

How Reliable are Model Diagnostics?

Aribandi, V., Tay, Y., & Metzler, D. (2021) · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

Topic ModelingNatural Language Processing Techniques

Cited by 15

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

Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models

Padlewski, P., Bain, M., Henderson, M., Zhu, Z., Relan, N., Pham, H., Ong, D., Aleksiev, K., Ormazabal, A., Phua, S., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 1

Symbol tuning improves in-context learning in language models

Wei, J., Hou, L., Lampinen, A., Chen, X., Huang, D., Tay, Y., Chen, X., Lu, Y., Zhou, D., Ma, T., et al. (2023) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 1