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Antoine Bosselut
@ABosselut
Helping machines make sense of the world. Asst Prof @ICepfl; Before: @stanfordnlp @allen_ai @uwnlp @MSFTResearch #NLProc #AI
Joined March 2013
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    The next generation of open LLMs should be inclusive, compliant, and multilingual by design. That’s why we (@EPFL @ETH_en) built Apertus.
    @EPFL , @ETH_en and #CSCS today released Apertus, Switzerland's first large-scale, multilingual language model (LLM). As a fully open LLM, it serves as a building block for developers and organizations to create their own applications: cscs.ch/science/comput… #Apertus #AI
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    I’m excited to announce that I’ll be joining the @ICepfl School at @EPFL_en as an assistant professor in Fall 2021! I’m looking forward to working with the students, faculty, and researchers there, and in the broader #EurNLP community.
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    The next few years are going to be critical for setting the norms for safe deployment and societal integration of AI. We've launched the #SwissAI initiative to meet this challenge.
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    Check out our Meditron-7B & 70B #LLMs adapted for medicine. Test them, break them, and help us find ways to make them better. AI safety only moves forward with open models and community efforts. Don't use MEDITRON in real world apps without further testing and alignment.
    We present MEDITRON, a set of new open-access #LLMs (70B & 7B) adapted to the medical domain, achieving new SoTA open-source performance on common medical benchmarks, outperforming #GPT-3.5 and Med-PaLM, and coming within 5% of #GPT4 Find out how we did this ⬇️
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    I’ll be building up a new #NLProc group at @ICepfl starting in Fall 2021! Apply to the EDIC PhD program if you’re interested in challenges at the intersection of NLP, commonsense reasoning, and knowledge representations.
    Antoine Bosselut (@ABosselut) has openings for #PhD students in his group. Find out more about his #research at: atcbosselut.github.io, and learn more about our @EPFL #EDIC #computerscience PhD program: go.epfl.ch/phd-edic
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    It’s an honor to have been named to the #ForbesUnder30 Europe list in Science & Healthcare. Looking forward to joining @ICepfl @EPFL in a few months and growing research thrusts in #NLProc, knowledge representations, and reasoning.
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    (1/n) Can machines make commonsense predictions? ☄️COMET☄️can! (arxiv.org/abs/1906.05317). Check out new work from @uwnlp and @allen_ai with Hannah Rashkin, @MaartenSap , @cmalaviya11 , @real_asli , and @YejinChoinka appearing at @ACL2019_Italy
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    NEW PAPER ALERT: Many #NLProc systems integrate external commonsense, but do they retrieve relevant knowledge for this integration? Our #EMNLP2022 Findings paper proposes ComFact, a challenging dataset for linking contextually-relevant commonsense to natural language contexts
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    I will be taking on new PhD students next Fall. Apply to the EDIC program if you’re interested in challenges at the intersection of #NLProc, reasoning, and knowledge representation. Come work with me, Deniz, and the @ICepfl NLP lab!
    The Natural Language Processing Lab is looking for #PhD students. Find out more about Deniz's #research at atcbosselut.github.io , and about our world-leading @EPFL #EDIC #computerscience PhD program: go.epfl.ch/phd-edic @ABosselut
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    🙌 👉 @YejinChoinka changed the trajectory of my PhD -- which changed my life!
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    Hey folks, I'll be presenting a poster on our work "Dynamic Neuro-Symbolic Knowledge Graph Construction for Zero-shot Commonsense Question Answering" at the AAAI poster session this morning and evening (BC-D4-R2).
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    NEW SOFTWARE: Have you wanted to use #NLProc knowledge models (like COMET), but don't know how to get started? Well, look no more! Our new python toolkit kogito (github.com/epfl-nlp/kogito) provides an intuitive and extensible starting point to interact with knowledge models.
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    Hey everyone, I’m excited to announce “Efficient Adaptation of Pretrained Transformers for Abstractive Summarization,” a work by Andrew Hoang, myself, @real_asli and @YejinChoinka. arxiv.org/abs/1906.00138 1/
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    My new favorite game: is it motivational quote or a tip for effective reinforcement learning?
    Assigning credit is less about rewards, and more about assigning influence for future decisions. Attribution is crucial, but for different reasons than one might think.