Skip to content
View EachSheep's full-sized avatar
🎯
Focusing
🎯
Focusing

Highlights

  • Pro

Block or report EachSheep

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
eachsheep/README.md

Hi thereπŸ‘‹

GitHub RSS

Short Bio

  • πŸŽ“ From September 2022, Haiyang started his Ph.D. degree in computer software and theory in School of Computer Science of Peking University.

  • πŸ… Haiyang received his B.E degree from School of Computer Science in Northwestern Polytechnical University in June 2022.

  • 🌱 My research interests lie in agents based on large models (LLMs/MLMs). Specifically, I am interested in:

    • πŸ”— The integration of LMs with APIs (tools).
    • πŸ›  The software engineering challenges associated with the integration.
    • πŸ“± The applications of LMs on edge devices.
  • πŸ“š My research group primarily focuses on system software, including machine learning systems, serverless computing, web systems, software engineering, and etc. In my first year of Ph.D., I studied anomaly detection, federated learning, inference optimization for LLMs in the cloud, etc.

  • πŸ” Throughout my studies from system software to deep learning, I have gained knowledge in various areas including methods and applications of natural language processing, retrieval systems, data analysis and mining, acceleration, and application of machine learning systems.

πŸ“« Correspondence

🌟 Others

  • πŸ–‹ My introduction at here.

πŸ““ Gists I wrote

⭐ Recent Stars

  • fifty-six/Scarab - An installer for Hollow Knight mods written in Avalonia. (1 week ago)
  • Hongcheng-Gao/Awesome-Long2short-on-LRMs - Awesome-Long2short-on-LRMs is a collection of state-of-the-art, novel, exciting long2short methods on large reasoning models. It contains papers, codes, datasets, evaluations, and analyses. (1 month ago)
  • aqpower/obsidian-Latex2MathJax - Convert LaTeX math formulas generated by large models (e.g., ChatGPT) into MathJax format supported by Markdown. (1 month ago)
  • MIT-MI/MEM1 - (1 month ago)
  • StigLidu/DualDistill - [EMNLP 2025] The official implementation for paper "Agentic-R1: Distilled Dual-Strategy Reasoning" (1 month ago)

Pinned Loading

  1. gta0804/MASS gta0804/MASS Public

    Official implementation of MASS: Multi-Agent Simulation Scaling for Portfolio Construction

    Python 148 17

  2. ShortcutsBench ShortcutsBench Public

    ShortcutsBench: A Large-Scale Real-World Benchmark for API-Based Agents

    Python 103 4

  3. RAGSynth RAGSynth Public

    The implementation of RAGSynth: Synthetic Data for Robust and Faithful RAG Component Optimization

    Python 17 3

  4. blog blog Public

    My personal introduction

    HTML 1

  5. AbnormalDetection AbnormalDetection Public

    ADPal: Automatic Detection of Troubled Users in Online Service Systems via Page Access Logs

    Python 1