يعرض 41 - 60 نتائج من 269 نتيجة بحث عن '(( python code presented ) OR ( python study presented ))', وقت الاستعلام: 0.29s تنقيح النتائج
  1. 41
  2. 42
  3. 43
  4. 44
  5. 45
  6. 46
  7. 47
  8. 48
  9. 49
  10. 50
  11. 51
  12. 52
  13. 53

    Overview of one حسب Guillermo Pérez-Hernández (21156182)

    منشور في 2025
    الموضوعات:
  14. 54

    PyGMT – Accessing and Integrating GMT with Python and the Scientific Python Ecosystem (AGU24, U12B-05) حسب Yvonne Fröhlich (20442683)

    منشور في 2024
    "…</p><p dir="ltr">PyGMT (<a href="https://www.pygmt.org/" target="_blank">https://www.pygmt.org/</a>) wraps around the very fast GMT C code to make it accessible through the Python programming language. …"
  15. 55

    Datasets To EVAL. حسب Jin Lu (428513)

    منشور في 2025
    "…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"
  16. 56

    Statistical significance test results. حسب Jin Lu (428513)

    منشور في 2025
    "…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"
  17. 57

    How RAG work. حسب Jin Lu (428513)

    منشور في 2025
    "…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"
  18. 58

    OpenBookQA experimental results. حسب Jin Lu (428513)

    منشور في 2025
    "…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"
  19. 59

    AI2_ARC experimental results. حسب Jin Lu (428513)

    منشور في 2025
    "…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"
  20. 60

    TQA experimental results. حسب Jin Lu (428513)

    منشور في 2025
    "…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"