World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
22721
World Ranking
5742
National Ranking
347

Research.com Recognitions

  • 2013 - Fellow of Alfred P. Sloan Foundation

Overview

Arthur Szlam is a researcher affiliated with DeepMind in the United Kingdom. Their work primarily spans the field of Computer Science, with a significant focus on Artificial Intelligence. Additional research areas include Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Molecular Biology, and aspects of Sociology and Political Science.

The scientist's research topics cover a range of themes such as Topic Modeling, Natural Language Processing Techniques, Speech and Dialogue Systems, Multimodal Machine Learning Applications, Domain Adaptation and Few-Shot Learning, Advanced Image and Video Retrieval Techniques, and Explainable Artificial Intelligence (XAI).

Arthur Szlam has been involved in numerous publications, with a strong presence in several key academic venues. These include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Transactions of the Association for Computational Linguistics
  • Findings of the Association for Computational Linguistics: NAACL 2022

Among their recent papers are:

  • BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage, 2022, arXiv (Cornell University)
  • Beyond Goldfish Memory: Long-Term Open-Domain Conversation, 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Hash Layers For Large Sparse Models, 2021, arXiv (Cornell University)
  • Reducing Conversational Agents' Overconfidence Through Linguistic Calibration, 2022, Transactions of the Association for Computational Linguistics
  • Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions, 2020, arXiv (Cornell University)

Frequent co-authors collaborating with Arthur Szlam include Jason Weston, Jack Urbanek, Kurt Shuster, Kavya Srinet, and Emily Dinan.

Arthur Szlam was awarded the Fellow of the Alfred P. Sloan Foundation in 2013.

Best Publications

  • Spectral Networks and Locally Connected Networks on Graphs

    Joan Bruna;Wojciech Zaremba;Arthur Szlam;Yann LeCun

  • Geometric Deep Learning: Going beyond Euclidean data

    Michael M. Bronstein;Joan Bruna;Yann LeCun;Arthur Szlam

  • End-to-end memory networks

    Sainbayar Sukhbaatar;Arthur Szlam;Jason Weston;Rob Fergus

  • Deep generative image models using a Laplacian pyramid of adversarial networks

    Emily Denton;Soumith Chintala;Arthur Szlam;Rob Fergus

  • Personalizing Dialogue Agents: I have a dog, do you have pets too?

    Saizheng Zhang;Emily Dinan;Jack Urbanek;Arthur Szlam

  • Learning multiagent communication with backpropagation

    Sainbayar Sukhbaatar;Arthur Szlam;Rob Fergus

  • Video (language) modeling: a baseline for generative models of natural videos.

    Marc'Aurelio Ranzato;Arthur Szlam;Joan Bruna;Michaël Mathieu

  • A Randomized Algorithm for Principal Component Analysis

    Vladimir Rokhlin;Arthur Szlam;Mark Tygert

  • The Second Conversational Intelligence Challenge (ConvAI2)

    Emily Dinan;Varvara Logacheva;Valentin Malykh;Alexander H. Miller

  • Incremental gradient on the Grassmannian for online foreground and background separation in subsampled video

    Jun He;Laura Balzano;Arthur Szlam

  • Simple Baseline for Visual Question Answering

    Bolei Zhou;Yuandong Tian;Sainbayar Sukhbaatar;Arthur Szlam

  • Optimizing the Latent Space of Generative Networks

    Piotr Bojanowski;Armand Joulin;David Lopez-Paz;Arthur Szlam

  • Dialogue natural language inference

    Sean Welleck;Jason Weston;Jason Weston;Arthur Szlam;Kyunghyun Cho

  • BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage

    Unknown

  • Hybrid Linear Modeling via Local Best-Fit Flats

    Teng Zhang;Arthur Szlam;Yi Wang;Gilad Lerman

  • Tracking the World State with Recurrent Entity Networks

    Mikael Henaff;Mikael Henaff;Jason Weston;Arthur Szlam;Antoine Bordes

  • Intrinsic motivation and automatic curricula via asymmetric self-play

    Sainbayar Sukhbaatar;Zeming Lin;Ilya Kostrikov;Gabriel Synnaeve

  • Median K-Flats for hybrid linear modeling with many outliers

    Teng Zhang;Arthur Szlam;Gilad Lerman

  • Diffusion wavelet packets

    James C. Bremer;Ronald R. Coifman;Mauro Maggioni;Arthur D. Szlam

  • Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems

    Jesse Dodge;Andreea Gane;Xiang Zhang;Antoine Bordes

  • Regularization on Graphs with Function-adapted Diffusion Processes

    Arthur D. Szlam;Mauro Maggioni;Ronald R. Coifman

Frequent Co-Authors

Jason Weston
Jason Weston Facebook (United States)
Rob Fergus
Rob Fergus New York University
Yann LeCun
Yann LeCun Facebook (United States)
Marc'Aurelio Ranzato
Marc'Aurelio Ranzato DeepMind (United Kingdom)
Joan Bruna
Joan Bruna New York University
Douwe Kiela
Douwe Kiela Stanford University
Xavier Bresson
Xavier Bresson National University of Singapore
Myle Ott
Myle Ott Facebook (United States)
Ronald R. Coifman
Ronald R. Coifman Yale University

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