World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
31
Citations
6453
World Ranking
13412
National Ranking
5365

Overview

Noam Slonim is affiliated with IBM in the United States and has contributed extensively to the field of computer science, with a focus on artificial intelligence. Their research spans several interconnected subfields, including artificial intelligence, information systems, sociology and political science, health, and applied psychology.

The central areas of their work cover a range of topics:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Sentiment Analysis and Opinion Mining
  • Advanced Text Analysis Techniques
  • Software Engineering Research
  • Machine Learning and Data Classification
  • Machine Learning and Algorithms

Slonim's publication record features several recent papers showcasing developments in natural language processing and autonomous systems. These include:

  • "An autonomous debating system," 2021, Nature
  • "Efficient Methods for Natural Language Processing: A Survey," 2023, Transactions of the Association for Computational Linguistics
  • "Usability and Credibility of a COVID-19 Vaccine Chatbot for Young Adults and Health Workers in the United States: Formative Mixed Methods Study," 2022, JMIR Human Factors
  • "Chatbot-Delivered COVID-19 Vaccine Communication Message Preferences of Young Adults and Public Health Workers in Urban American Communities: Qualitative Study," 2022, Journal of Medical Internet Research
  • "Quality Controlled Paraphrase Generation," 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Their work has been cited with varying frequency, with the autonomous debating system paper attracting significant attention.

Slonim frequently collaborates with a core group of coauthors, reflecting established research partnerships. These include:

  • Yoav Katz
  • Ranit Aharonov
  • Liat Ein-Dor
  • Leshem Choshen
  • Ariel Gera

The venues where Slonim most commonly publishes highlight the arenas of scholarly communication they engage with. Key publication venues 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)
  • Nature
  • Transactions of the Association for Computational Linguistics

Best Publications

  • Document clustering using word clusters via the information bottleneck method

    Noam Slonim;Naftali Tishby

  • Agglomerative Information Bottleneck

    Noam Slonim;Naftali Tishby

  • A Universal Framework for Regulatory Element Discovery across All Genomes and Data Types

    Olivier Elemento;Noam Slonim;Saeed Tavazoie

  • Unsupervised document classification using sequential information maximization

    Noam Slonim;Nir Friedman;Naftali Tishby

  • The Power of Word Clusters for Text Classification

    Noam Slonim;Naftali Tishby

  • Information-based clustering.

    Noam Slonim;Gurinder Singh Atwal;Gašper Tkačik;William Bialek

  • Glucose regulates transcription in yeast through a network of signaling pathways

    Shadia Zaman;Soyeon I Lippman;Lisa Schneper;Noam Slonim

  • Show Me Your Evidence - an Automatic Method for Context Dependent Evidence Detection

    Ruty Rinott;Lena Dankin;Carlos Alzate Perez;Mitesh M. Khapra

  • Predicting Customer Churn in Mobile Networks Through Analysis of Social Groups

    Yossi Richter;Elad Yom-Tov;Noam Slonim

  • An autonomous debating system.

    Noam Slonim;Yonatan Bilu;Carlos Alzate;Roy Bar-Haim

  • Context Dependent Claim Detection

    Ran Levy;Yonatan Bilu;Daniel Hershcovich;Ehud Aharoni

  • Data Clustering by Markovian Relaxation and the Information Bottleneck Method

    Naftali Tishby;Noam Slonim

  • Multivariate Information Bottleneck

    Nir Friedman;Ori Mosenzon;Noam Slonim;Naftali Tishby

  • A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics

    Ehud Aharoni;Anatoly Polnarov;Tamar Lavee;Daniel Hershcovich

  • Stance Classification of Context-Dependent Claims

    Roy Bar-Haim;Indrajit Bhattacharya;Francesco Dinuzzo;Amrita Saha

  • Active Learning for BERT: An Empirical Study

    Liat Ein-Dor;Alon Halfon;Ariel Gera;Eyal Shnarch

  • Efficient Methods for Natural Language Processing: A Survey

    Unknown

  • Multivariate information bottleneck

    Noam Slonim;Nir Friedman;Naftali Tishby

  • Method and system for evaluating a machine tool operating characteristics

    Ehud Aharoni;Robert J. Baseman;Ramona Kei;Oded Margalit

  • Objective Classification of Galaxy Spectra using the Information Bottleneck Method

    Noam Slonim;Rachel Somerville;Rachel Somerville;Naftali Tishby;Ofer Lahav;Ofer Lahav

  • A Large-Scale Dataset for Argument Quality Ranking: Construction and Analysis

    Shai Gretz;Roni Friedman;Edo Cohen-Karlik;Assaf Toledo

  • Automatic Argument Quality Assessment - New Datasets and Methods.

    Assaf Toledo;Shai Gretz;Edo Cohen-Karlik;Roni Friedman

  • Ab initio genotype–phenotype association reveals intrinsic modularity in genetic networks

    Noam Slonim;Olivier Elemento;Saeed Tavazoie

Frequent Co-Authors

Naftali Tishby
Naftali Tishby Hebrew University of Jerusalem
Nir Friedman
Nir Friedman Weizmann Institute of Science
Iryna Gurevych
Iryna Gurevych Technical University of Darmstadt
Elad Yom-Tov
Elad Yom-Tov Microsoft (United States)
Ofer Lahav
Ofer Lahav University College London
Rachel S. Somerville
Rachel S. Somerville Flatiron Institute
Chris Reed
Chris Reed University of Dundee
William Bialek
William Bialek Princeton University
Olivier Elemento
Olivier Elemento Cornell University
James R. Broach
James R. Broach Pennsylvania State University

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