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    Using process rewards to train LLMs for better search reasoning

    Training large language models (LLMs) to improve search reasoning often involves process rewards-a technique that evaluates and reinforces step-by-step reasoning rather than just final answers. This approach enhances accuracy in complex tasks like math problems, logical deductions, and multi-step…
    Thumbnail Image of Tutorial Using process rewards to train LLMs for better search reasoning
    Image of Author Dr. Dipen
    Dr. Dipen
    I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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      Mitigating bias in LLM‑based scoring of English language learners

      Mitigating bias in LLM-based scoring for English language learners (ELLs) requires a structured approach to ensure fairness and accuracy. Below is a summary of key strategies, challenges, and outcomes based on recent research. Different LLMs employ varied bias mitigation methods. For example, GPT-4…
      Thumbnail Image of Tutorial Mitigating bias in LLM‑based scoring of English language learners
      Image of Author Dr. Dipen
      Dr. Dipen
      I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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        What Is Prompt Chaining and How to Use It

        Prompt chaining is a method where complex tasks are broken into sequential subtasks, each handled by a distinct prompt. This approach ensures context is preserved between steps and allows for structured problem-solving. Below is a breakdown of key aspects, techniques, and applications. Benefits:…
        Thumbnail Image of Tutorial What Is Prompt Chaining and How to Use It
        Image of Author Dr. Dipen
        Dr. Dipen
        I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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          How to Chain Prompts for Better LLM Flow

          Watch: Let The LLM Write The Prompt 2025 | Design Perfect Prompts for AI Agent | Prompt Mistakes (PART 1/7) by Amine DALY Prompt chaining enhances large language model (LLM) workflows by linking prompts sequentially or in parallel to solve complex tasks. This section breaks down techniques,…
          Thumbnail Image of Tutorial How to Chain Prompts for Better LLM Flow
          Image of Author Dr. Dipen
          Dr. Dipen
          I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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            AI Bootcamp Success Checklist: Fine-Tuning Instructions for Real-World Application Development

            Watch: Prompt Engineering by Thinking Neuron The LSU Online AI Bootcamp spans 26 weeks with 200+ hours of live classes and 15+ projects, focusing on Python, TensorFlow, and OpenAI. The Virginia Tech Bootcamp emphasizes machine learning and neural networks but lacks real-time project demos. In…
            Thumbnail Image of Tutorial AI Bootcamp Success Checklist: Fine-Tuning Instructions for Real-World Application Development
            Image of Author Dr. Dipen
            Dr. Dipen
            I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
            •Last Updated:
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