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Nenad Tomasev
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Nenad Tomasev
@weballergy
Senior staff research scientist at DeepMind. Opinions are my own. Re-tweets and favorites not to be considered as endorsements.
London, England
linkedin.com/in/nenadtomasev
Joined May 2009
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    Nenad Tomasev
    @weballergy
    Feb 13
    Excited to share our work on envisioning Intelligent AI Delegation (arxiv.org/abs/2602.11865). Delegation in most existing AI systems is brittle, and relies on simplified hand-crafted control flows. As such, it fails to meet the requirements of what is needed to truly scale
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    arxiv.org
    Intelligent AI Delegation
    AI agents are able to tackle increasingly complex tasks. To achieve more ambitious goals, AI agents need to be able to meaningfully decompose problems into manageable sub-components, and safely...
    8K
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    Nenad Tomasev
    @weballergy
    Nov 18, 2021
    Deep learning models are often perceived as black boxes. In our most recent work, Acquisition of Chess Knowledge in AlphaZero arxiv.org/abs/2111.09259 , we try to unpack how AlphaZero represents knowledge, where it resides within the network, and when it is acquired in training
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    Nenad Tomasev
    @weballergy
    Oct 28, 2024
    I'm happy to share that I got promoted to the role of Senior Staff Research Scientist here at Google DeepMind. It's been an incredibly exciting year, though the truly exciting work, as always, lies ahead.
    31K
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    Nenad Tomasev
    @weballergy
    Dec 5, 2024
    I'm excited to share a new paper: "Mastering Board Games by External and Internal Planning with Language Models" storage.googleapis.com/deepmind-media… (also soon to be up on Arxiv, once it's been processed there)
    152K
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    Nenad Tomasev
    @weballergy
    Jun 1, 2017
    'Adversarial Generation of Natural Language': producing realistic sentences arxiv.org/abs/1705.10929 #deeplearning #machinelearning #NLP #AI
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    Nenad Tomasev
    @weballergy
    Aug 3, 2017
    DeepMoji: Predicting emojis for classifying text sentiment/emotion/sarcasm arxiv.org/abs/1708.00524 #NLP #deeplearning #AI
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    Nenad Tomasev
    @weballergy
    Jun 6, 2018
    'Relational recurrent neural networks': performing complex relational reasoning in memory networks. arxiv.org/abs/1806.01822 #DeepLearning #AI #MachineLearning
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    Nenad Tomasev
    @weballergy
    May 31, 2018
    "To Trust Or Not To Trust A Classifier" by Google Research arxiv.org/abs/1805.11783 : beyond simple confidence scores. The ability to auto-detect bad predictions in critical for safe deployments in sensitive applications. #MachineLearning #DataScience #AI
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    arxiv.org
    To Trust Or Not To Trust A Classifier
    Knowing when a classifier's prediction can be trusted is useful in many applications and critical for safely using AI. While the bulk of the effort in machine learning research has been towards...
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    Nenad Tomasev
    @weballergy
    Jul 31, 2019
    Proud to share the results of our work on applying deep learning for early prediction of future acute kidney injury from electronic health records in our collaboration with the US Department of Veterans Affairs - just published in Nature: nature.com/articles/s4158…
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    Nenad Tomasev
    @weballergy
    Sep 4, 2017
    'Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning' arxiv.org/abs/1709.00103 #MachineLearning
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    Nenad Tomasev
    @weballergy
    Jun 14, 2018
    'A Probabilistic U-net for Segmentation of Ambiguous Images': a cool new paper by my colleagues at DeepMind on how to deal with uncertainty in segmentation models. arxiv.org/abs/1806.05034 #DeepLearning #MachineLearning
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    Nenad Tomasev
    @weballergy
    Apr 6, 2018
    'Hyperbolic Entailment Cones for Learning Hierarchical Embeddings': viewing hierarchical relations as partial orders based on a family of nested geodesically convex cones arxiv.org/abs/1804.01882 #AI #MachineLearning
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    Nenad Tomasev
    @weballergy
    Oct 4, 2017
    'Dilated Convolutions for Modeling Long-Distance Genomic Dependencies' arxiv.org/abs/1710.01278 #DeepLearning #Genomics #AI
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    Nenad Tomasev
    @weballergy
    Jul 24, 2017
    'A Distributional Perspective on Reinforcement Learning': modeling the full distribution of return. arxiv.org/abs/1707.06887 #machinelearning
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