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Computer Science

D-Index
66
Citations
22152
World Ranking
2282
National Ranking
44

Overview

Ido Dagan is affiliated with Bar-Ilan University in Israel. Their research primarily falls within the field of Computer Science, with a particular focus on Artificial Intelligence. Other subfields addressed in their work include Computer Vision and Pattern Recognition, Computer Networks and Communications, Computer Science Applications, and Molecular Biology.

Their research covers an array of topics related to natural language processing and text analysis. Notable themes in their publications encompass Topic Modeling, Natural Language Processing Techniques, Advanced Text Analysis Techniques, Speech and Dialogue Systems, Multimodal Machine Learning Applications, Semantic Web and Ontologies, and Text and Document Classification Technologies.

Frequent co-authors who have collaborated with Ido Dagan include Arie Cattan, Avi Caciularu, Ori Shapira, Aviv Slobodkin, and Ori Ernst.

Key venues where they have published include arXiv (Cornell University), the Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Transactions of the Association for Computational Linguistics, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, and AI Magazine.

Selected recent papers authored or co-authored by Ido Dagan are:

  • Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes (2021), Transactions of the Association for Computational Linguistics
  • Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling (2020), Deep Blue (University of Michigan)
  • Asking It All: Generating Contextualized Questions for any Semantic Role (2021), Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Proposition-Level Clustering for Multi-Document Summarization (2022), Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Long Context Question Answering via Supervised Contrastive Learning (2022), Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Best Publications

  • Improving Distributional Similarity with Lessons Learned from Word Embeddings

    Omer Levy;Yoav Goldberg;Ido Dagan

  • The PASCAL Recognising Textual Entailment Challenge

    Ido Dagan;Oren Glickman;Bernardo Magnini

  • The Third PASCAL Recognizing Textual Entailment Challenge

    Danilo Giampiccolo;Bernardo Magnini;Ido Dagan;Bill Dolan

  • Knowledge discovery in Textual Databases (KDT)

    Ronen Feldman;Ido Dagan

  • Committee-based sampling for training probabilistic classifiers

    Ido Dagan;Sean P. Engelson

  • The Seventh PASCAL Recognizing Textual Entailment Challenge.

    Luisa Bentivogli;Peter Clark;Ido Dagan;Danilo Giampiccolo

  • Similarity-Based Models of Word Cooccurrence Probabilities

    Ido Dagan;Lillian Lee;Fernando C. N. Pereira

  • context2vec: Learning Generic Context Embedding with Bidirectional LSTM

    Oren Melamud;Jacob Goldberger;Ido Dagan

  • Word sense disambiguation using a second language monolingual corpus

    Ido Dagan;Alon Itai

  • Contextual word similarity and estimation from sparse data

    Ido Dagan;Shaul Marcus;Shaul Markovitch

  • Termight: Identifying and Translating Technical Terminology

    Ido Dagan;Ken Church

  • Recognizing textual entailment: Rational, evaluation and approaches – Erratum

    Ido Dagan;Bill Dolan;Bernardo Magnini;Dan Roth

  • Recognizing Textual Entailment: Models and Applications

    Ido Dagan;Dan Roth;Mark Sammons;Fabio Massimo Zanzotto

  • Do Supervised Distributional Methods Really Learn Lexical Inference Relations

    Omer Levy;Steffen Remus;Chris Biemann;Ido Dagan

  • Two Languages Are More Informative Than One

    Ido Dagan;Alon Itai;Ulrike Schwall

  • PROBABILISTIC TEXTUAL ENTAILMENT: GENERIC APPLIED MODELING OF LANGUAGE VARIABILITY

    Ido Dagan;Oren Glickman

  • Supervised Open Information Extraction

    Gabriel Stanovsky;Julian Michael;Luke Zettlemoyer;Ido Dagan

  • Robust Bilingual Word Alignment for Machine Aided Translation

    Ido Dagan;Kenneth Ward Church;Willian Gale

  • Directional distributional similarity for lexical inference

    Lili Kotlerman;Ido Dagan;Idan Szpektor;Maayan Zhitomirsky-geffet

  • Ranking Generated Summaries by Correctness: An Interesting but Challenging Application for Natural Language Inference

    Tobias Falke;Leonardo F. R. Ribeiro;Prasetya Ajie Utama;Ido Dagan

  • Synthesis Lectures on Human Language Technologies

    Ido Dagan;Dan Roth;Mark Sammons;Fabio Massimo Zanzotto

Frequent Co-Authors

Jacob Goldberger
Jacob Goldberger Bar-Ilan University
Bernardo Magnini
Bernardo Magnini Fondazione Bruno Kessler
Iryna Gurevych
Iryna Gurevych Technical University of Darmstadt
Jonathan Berant
Jonathan Berant Tel Aviv University
Yoav Goldberg
Yoav Goldberg Bar-Ilan University
Omer Levy
Omer Levy Deep Mind
Dan Roth
Dan Roth University of Pennsylvania
Moshe Koppel
Moshe Koppel Bar-Ilan University
Lillian Lee
Lillian Lee Cornell University
Fernando Pereira
Fernando Pereira Google (United States)

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