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Researcher profile

Tao Xie

6 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. The Construction of Education Cloud Environment for Interactive Teaching

    2017

    Information technology, which is not only the aided teaching tool but has also become the platform supporting the new teaching mode, is changing the traditional teaching structure to the new student-centered one. Especially with the …

  2. ORIC: A Self-Adjusting Blockchain Protocol with High Throughput

    2021

    This paper presents a simple and self-adjusting blockchain protocol called ORIC to make full use of the available bandwidth as far as possible. ORIC follows the Nakamoto protocol and allows many more blocks to be …

  3. Effective Random Test Generation for Deep Learning Compilers

    2023 · arXiv (Cornell University)

    Deep learning compilers help address the difficulties of deploying deep learning models on diverse types of hardware. Testing deep learning compilers is highly crucial, because they are impacting countless AI applications that use them for …

  4. Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression Against Heterogeneous Attacks Toward AI Software Deployment

    2024 · IEEE Transactions on Software Engineering

    The size of deep learning models in artificial intelligence (AI) software is increasing rapidly, which hinders the large-scale deployment on resource-restricted devices (e.g., smartphones). To mitigate this issue, AI software compression plays a crucial role, …

  5. CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models

    2024

    Code generation models based on the pre-training and fine-tuning paradigm have been increasingly attempted by both academia and industry, resulting in well-known industrial models such as Codex, CodeGen, and PanGu-Coder. To evaluate the effectiveness of …

  6. DeepServe: Serverless Large Language Model Serving at Scale

    2025 · arXiv (Cornell University)

    In this paper, we propose DEEPSERVE, a scalable and serverless AI platform designed to efficiently serve large language models (LLMs) at scale in cloud environments. DEEPSERVE addresses key challenges such as resource allocation, serving efficiency, …