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coffee 'n' code </☕️>
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@medivo @instantlabs @GoPythonSoftware @SabzQalam

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hasaniqbal777/README.md

Making LLMs fact-check themselves, so you don't have to.

I'm a PhD student in NLP at MBZUAI, building systems that automatically verify the factual accuracy of large language models. My work spans factuality evaluation, iterative fact-checking, and machine-generated text detection. Here are some of my publications:

  • OpenFactCheck: A Unified Framework for Factuality Evaluation of LLMs. EMNLP 2024. [link]
  • OpenFactCheck: Building, Benchmarking Customized Fact-Checking Systems and Evaluating the Factuality of Claims and LLMs. COLING 2025. [link]
  • FIRE: Fact-checking with Iterative Retrieval and Verification. NAACL 2025. [link]
  • UrduFactCheck: An Agentic Fact-Checking Framework for Urdu with Evidence Boosting and Benchmarking. EMNLP 2025. [link]

Open to research collaborations. Feel free to reach out.

LinkedIn Google Scholar ORCID

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  1. openfactcheck-research/openfactcheck openfactcheck-research/openfactcheck Public

    An Open-source Factuality Evaluation Demo for LLMs

    HCL 23 5

  2. openfactcheck-research/urdufactcheck openfactcheck-research/urdufactcheck Public

    An Agentic Fact-Checking Framework for Urdu with Evidence Boosting and Benchmarking

    Jupyter Notebook 2

  3. MetumpX-bin MetumpX-bin Public

    🍃 A Metabolomics Support Package for Untargeted Mass Spectrometery

    R 3

  4. coling-2025 coling-2025 Public

    Repository for the COLING 2025 Official website

    JavaScript 4 1

  5. COVID-19_Vaccine_Correlation_Study COVID-19_Vaccine_Correlation_Study Public

    A Correlation Study of COVID-19 in Europe Considering Different Vaccines, Age Groups and Variants

    Jupyter Notebook

  6. streamlit-blockly streamlit-blockly Public

    Streamlit Google Blockly Component

    Vue 5