Yang Tan

Master Student @ECUST

Shanghai, China
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Recent Posts

  • PaperNote

    Movie Gen:A Cast of Media Foundation Models

    2025-06-05

  • PaperNote

    NeurIPSw-2024 Mixture of Experts Enable Efficient and Effective Protein Understanding and Design

    2025-05-26

  • PaperNote

    NeurIPS-2023 Predicting a Protein’s Stability under a Million Mutations

    2025-05-23

  • PaperNote

    Scaling unlocks broader generation and deeper functional understanding of proteins

    2025-04-19

  • PaperNote

    Prot42:a Novel Family of Protein Language Models for Target-aware Protein Binder Generation

    2025-04-10

OpenAI-2020 Language Models are Few-Shot Learners

Mar 21 PaperNote CL Comments Word Count: 1.2k(words) Read Count: 4(minutes)

ASE-2020 Automating just-in-time comment updating

Mar 6 PaperNote CL, SE Comments Word Count: 479(words) Read Count: 1(minutes)

IJCAI-2019 Commit Message Generation for Source Code Changes

Mar 5 PaperNote CL, SE Comments Word Count: 365(words) Read Count: 1(minutes)

ICLR-2021 Retrieval-Augmented Generation for Code Summarization via Hybrid GNN

Feb 28 PaperNote CL, SE Comments Word Count: 756(words) Read Count: 3(minutes)

ACL-2021 Learning Sequential and Structural Information for Source Code Summarization

Feb 28 PaperNote CL, SE Comments Word Count: 256(words) Read Count: 1(minutes)

PyTorch-matmul函数

Feb 27 DeepLearning pytorch Comments Word Count: 1.3k(words) Read Count: 5(minutes)

NIPS-2014 Two-Stream Convolutional Networks for Action Recognition in Videos

Feb 25 PaperNote CV Comments Word Count: 704(words) Read Count: 2(minutes)

ICSME-2021 Ensemble Models for Neural Source Code Summarization of Subroutines

Feb 21 PaperNote CL, SE Comments Word Count: 272(words) Read Count: 1(minutes)

ICSE-2019 A Novel Neural Source Code Representation Based on Abstract Syntax Tree

Feb 17 PaperNote CL, SE Comments Word Count: 668(words) Read Count: 2(minutes)

ICSE-2019 A Neural Model for Generating Natural Language Summaries of Program Subroutines

Feb 16 PaperNote CL, SE Comments Word Count: 178(words) Read Count: 1(minutes)

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