Personal profile

About Me

Ido Dagan holds B.Sc. (Summa Cum Laude) and Ph.D. degrees in Computer Science from the Technion, Israel. He conducted his Ph.D. research in collaboration with the IBM Haifa Scientific Center, where he was a research fellow in 1991. During 1992-1994 he was a Member of Technical Staff at AT&T Bell Laboratories. During 1994-1998 he has been at the Department of Computer Science of Bar Ilan University, to which he returned in 2003. During 1998-2003 he was co-founder and CTO of a text categorization startup company, FocusEngine, and VP of Technology at LingoMotors, a Cambridge Massachusetts company which acquired FocusEngine.

His research interests for over a decade have been within empirical and learning methods for language processing, often operating over rich linguistic representations, with particular emphasis on unsupervised semantic learning. In the last few years he has introduced textual entailment as a generic framework for applied semantic inference over texts. With our colleagues, we organized the three rounds of the PASCAL Recognizing Textual Entailment (RTE) Challenges (2004-2007), which attracted dozens of research groups and became the primary forum for empirical evaluation of semantic inference systems. At the Bar Ilan NLP group he develops computational models of textual entailment, including automatic knowledge acquisition, semantic inference, and information extraction and retrieval applications.

Research Topics:

  • Natural language processing
  • Machine learning and statistical methods
  • Information retrieval and text analysis

Education/Academic qualification

PhD

Oct 1986Sep 1992

Award Date: 30 Sep 1992

Bachelor

Oct 1983Sep 1986

Award Date: 30 Sep 1986

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  • Agent-Initiated Interaction in Phone UI Automation

    Kahlon, N., Rom, G., Efros, A., Galgani, F., Berkovitch, O., Caduri, S., Bishop, W. E., Riva, O. & Dagan, I., 23 May 2025, WWW Companion 2025 - Companion Proceedings of the ACM Web Conference 2025. Association for Computing Machinery, Inc, p. 2391-2400 10 p. (WWW Companion 2025 - Companion Proceedings of the ACM Web Conference 2025).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Open Access
    1 Scopus citations
  • Identifying User Goals From UI Trajectories

    Berkovitch, O., Caduri, S., Kahlon, N., Efros, A., Caciularu, A. & Dagan, I., 23 May 2025, WWW Companion 2025 - Companion Proceedings of the ACM Web Conference 2025. Association for Computing Machinery, Inc, p. 2381-2390 10 p. (WWW Companion 2025 - Companion Proceedings of the ACM Web Conference 2025).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Open Access
  • LAQuer: Localized Attribution Queries in Content-grounded Generation

    Hirsch, E., Slobodkin, A., Wan, D., Stengel-Eskin, E., Bansal, M. & Dagan, I., 2025, Long Papers. Che, W., Nabende, J., Shutova, E. & Pilehvar, M. T. (eds.). Association for Computational Linguistics (ACL), p. 15355-15370 16 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics; vol. 1).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Attribute First, then Generate: Locally-attributable Grounded Text Generation

    Slobodkin, A., Hirsch, E., Cattan, A., Schuster, T. & Dagan, I., 2024, Long Papers. Ku, L.-W., Martins, A. F. T. & Srikumar, V. (eds.). Association for Computational Linguistics (ACL), p. 3309-3344 36 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics; vol. 1).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    6 Scopus citations
  • Efficient Data Generation for Source-grounded Information-seeking Dialogs: A Use Case for Meeting Transcripts

    Golany, L., Galgani, F., Mamo, M., Parasol, N., Vandsburger, O., Bar, N. & Dagan, I., 2024, EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024. Al-Onaizan, Y., Bansal, M. & Chen, Y.-N. (eds.). Association for Computational Linguistics (ACL), p. 1908-1925 18 p. (EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review