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๐Ÿ“š
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๐Ÿ“š
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@sissa @interpretingdl @AI-Student-Society @factcheck-it @inseq-team @Hugging-Face-Supporter @GroNLP

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gsarti/README.md

Welcome! ๐Ÿ™Œ

Portfolio Huggingface Hub Twitter LinkedIn Google Scholar

I am a PhD student at the University of Groningen GroNLP Lab and part of the project InDeep: Interpreting Deep Learning Models for Text and Sound, working mainly on interpretability for neural machine translation. Previously, I was a research intern at AWS AI Labs NYC, a research scientist at Aindo, a student in the Data Science MSc at University of Trieste & SISSA and a founding member of the AI Student Society.

My research focuses on interpretability for NLP models, particularly to the benefit of end-users and by leveraging human behavioral signals. I am also very passionate about open-source collaboration :octocat: and I currently lead the development of the Inseq toolkit for interpreting generative language models.

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  1. inseq-team/inseq inseq-team/inseq Public

    Interpretability for sequence generation models ๐Ÿ› ๐Ÿ”

    Python 386 36

  2. pecore pecore Public

    Materials for "Quantifying the Plausibility of Context Reliance in Neural Machine Translation" at ICLR'24 ๐Ÿ‘ ๐Ÿ‘

    Jupyter Notebook 13 1

  3. divemt divemt Public

    Materials for "DivEMT: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages" at EMNLP'22 ๐Ÿ—บ๏ธ

    HTML 7 1

  4. it5 it5 Public

    Materials for "IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation" ๐Ÿ‡ฎ๐Ÿ‡น

    Jupyter Notebook 30 4

  5. verbalized-rebus verbalized-rebus Public

    Materials for "Non Verbis, Sed Rebus: Large Language Models are Weak Solvers of Italian Rebuses" at CLiC-it'24 ๐Ÿงฉ

    Jupyter Notebook 3 1

  6. covid-papers-browser covid-papers-browser Public

    Browse Covid-19 & SARS-CoV-2 Scientific Papers with Transformers ๐Ÿฆ  ๐Ÿ“–

    CSS 182 27