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2025

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Computer Science

D-Index
53
Citations
15633
World Ranking
4723
National Ranking
2194

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Yi Tay is a researcher affiliated with Google in the United States, specializing in the field of computer science with a primary focus on artificial intelligence. Their research encompasses several subfields including computer vision and pattern recognition, information systems, electrical and electronic engineering, and signal processing.

The scientist's work spans numerous topics such as topic modeling, natural language processing techniques, multimodal machine learning applications, domain adaptation and few-shot learning, advanced neural network applications, speech recognition and synthesis, and text readability and simplification.

Yi Tay has published extensively, with a significant number of papers appearing in venues such as arXiv (Cornell University), the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), the Journal of Informatics and Web Engineering, ANZ Journal of Surgery, and ACM Computing Surveys.

Notable recent publications include:

  • PaLM: Scaling Language Modeling with Pathways (2022), arXiv (Cornell University)
  • Scaling Instruction-Finetuned Language Models (2022), arXiv (Cornell University)
  • Emergent Abilities of Large Language Models (2022), arXiv (Cornell University)
  • Efficient Transformers: A Survey (2022), ACM Computing Surveys
  • Efficient Transformers: A Survey (2020), arXiv (Cornell University)

Their collaboration network includes frequent co-authors, with the most notable being Donald Metzler, Dara Bahri, Mostafa Dehghani, Hyung Won Chung, and Vinh Q. Tran.

Best Publications

  • Scaling Instruction-Finetuned Language Models

    Unknown

  • Deep Learning Based Recommender System: A Survey and New Perspectives

    Shuai Zhang;Lina Yao;Aixin Sun;Yi Tay

  • Emergent Abilities of Large Language Models

    Unknown

  • Efficient Transformers: A Survey

    Yi Tay;Mostafa Dehghani;Dara Bahri;Donald Metzler

  • The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

    Unknown

  • Quaternion Knowledge Graph Embeddings

    Shuai Zhang;Yi Tay;Lina Yao;Qi Liu

  • Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

    Unknown

  • Latent Relational Metric Learning via Memory-based Attention for Collaborative Ranking

    Yi Tay;Luu Anh Tuan;Siu Cheung Hui

  • Multi-Pointer Co-Attention Networks for Recommendation

    Yi Tay;Anh Tuan Luu;Siu Cheung Hui

  • Multi-Pointer Co-Attention Networks for Recommendation.

    Yi Tay;Luu Anh Tuan;Siu Cheung Hui

  • Long Range Arena : A Benchmark for Efficient Transformers

    Yi Tay;Mostafa Dehghani;Samira Abnar;Yikang Shen

  • Synthesizer: Rethinking Self-Attention in Transformer Models

    Yi Tay;Dara Bahri;Donald Metzler;Da-Cheng Juan

  • Larger language models do in-context learning differently

    Unknown

  • Latent Relational Metric Learning via Memory-based Attention for Collaborative Ranking

    Yi Tay;Anh Tuan Luu;Siu Cheung Hui

  • Learning to Attend via Word-Aspect Associative Fusion for Aspect-Based Sentiment Analysis

    Yi Tay;Luu Anh Tuan;Siu Cheung Hui

  • Reasoning with Sarcasm by Reading In-Between

    Yi Tay;Anh Tuan Luu;Siu Cheung Hui;Jian Su

  • A New Generation of Perspective API: Efficient Multilingual Character-level Transformers

    Unknown

  • Language Models are Multilingual Chain-of-Thought Reasoners

    Unknown

  • SkipFlow: Incorporating Neural Coherence Features for End-to-End Automatic Text Scoring

    Yi Tay;Minh C. Phan;Luu Anh Tuan;Siu Cheung Hui

  • Sparse Sinkhorn Attention

    Yi Tay;Dara Bahri;Liu Yang;Donald Metzler

  • Compare, Compress and Propagate: Enhancing Neural Architectures with Alignment Factorization for Natural Language Inference

    Yi Tay;Anh Tuan Luu;Siu Cheung Hui

  • Learning to Rank Question Answer Pairs with Holographic Dual LSTM Architecture

    Yi Tay;Minh C. Phan;Luu Anh Tuan;Siu Cheung Hui

  • Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering

    Yi Tay;Luu Anh Tuan;Siu Cheung Hui

  • HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender Systems

    Lucas Vinh Tran;Yi Tay;Shuai Zhang;Gao Cong

  • Dyadic Memory Networks for Aspect-based Sentiment Analysis

    Yi Tay;Luu Anh Tuan;Siu Cheung Hui

  • Next Item Recommendation with Self-Attention

    Shuai Zhang;Yi Tay;Lina Yao;Aixin Sun

  • Translational Recommender Networks.

    Yi Tay;Anh Tuan Luu;Siu Cheung Hui

Frequent Co-Authors

Siu Cheung Hui
Siu Cheung Hui Nanyang Technological University
Donald Metzler
Donald Metzler Google (United States)
Lina Yao
Lina Yao Commonwealth Scientific and Industrial Research Organisation
Aixin Sun
Aixin Sun Nanyang Technological University
Yew-Soon Ong
Yew-Soon Ong Nanyang Technological University
Andrew Tomkins
Andrew Tomkins Google (United States)
Gao Cong
Gao Cong Nanyang Technological University
Jian Su
Jian Su Institute for Infocomm Research
Marc Najork
Marc Najork Google (United States)
Xiaoli Li
Xiaoli Li Singapore University of Technology and Design

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