World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
12193
World Ranking
5802
National Ranking
2637

Overview

Ralph Weischedel is affiliated with the University of Southern California in the United States. Their research primarily spans the field of Computer Science, with a focus on Artificial Intelligence and related subfields.

Their scholarly output includes work published in venues such as:

  • 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)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Key areas of study within their research comprise:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Management Science and Operations Research
  • General Decision Sciences
  • Management Information Systems

Their work addresses significant topics including:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Text Readability and Simplification
  • Artificial Intelligence in Games
  • Speech and Dialogue Systems
  • Intelligent Tutoring Systems and Adaptive Learning

Among their recent scholarly publications are:

  • Predictive Engagement: An Efficient Metric for Automatic Evaluation of Open-Domain Dialogue Systems, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Understanding Multimodal Procedural Knowledge by Sequencing Multimodal Instructional Manuals, 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Content Planning for Neural Story Generation with Aristotelian Rescoring, 2020, arXiv (Cornell University)
  • Perhaps PTLMs Should Go to School - A Task to Assess Open Book and Closed Book QA, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Learning to Generalize for Sequential Decision Making, 2020, arXiv (Cornell University)

Frequently, they collaborate with other researchers in their field, with notable coauthors including Marjorie Freedman, Nanyun Peng, Manuel R. Ciosici, Te-Lin Wu, and Dong-Ho Lee, reflecting a pattern of ongoing collaborative research efforts.

Best Publications

  • The Automatic Content Extraction (ACE) Program Tasks, Data, and Evaluation

    George R. Doddington;Alexis Mitchell;Mark A. Przybocki;Lance A. Ramshaw

  • An Algorithm that Learns What‘s in a Name

    Daniel M. Bikel;Richard Schwartz;Ralph M. Weischedel

  • OntoNotes: The 90% Solution

    Eduard Hovy;Mitchell Marcus;Martha Palmer;Lance Ramshaw

  • Nymble: a High-Performance Learning Name-finder

    Daniel M. Bikel;Scott Miller;Richard Schwartz;Ralph Weischedel

  • PERFORMANCE MEASURES FOR INFORMATION EXTRACTION

    John Makhoul;Francis Kubala;Richard Schwartz;Ralph Weischedel

  • Coping with ambiguity and unknown words through probabilistic models

    Ralph Weischedel;Richard Schwartz;Jeff Palmucci;Marie Meteer

  • CoNLL-2011 Shared Task: Modeling Unrestricted Coreference in OntoNotes

    Sameer Pradhan;Lance Ramshaw;Mitchell Marcus;Martha Palmer

  • Plan-And-Write: Towards Better Automatic Storytelling

    Lili Yao;Nanyun Peng;Ralph M. Weischedel;Kevin Knight

  • A New String-to-Dependency Machine Translation Algorithm with a Target Dependency Language Model

    Libin Shen;Jinxi Xu;Ralph Weischedel

  • A novel use of statistical parsing to extract information from text

    Scott Miller;Heidi Fox;Lance Ramshaw;Ralph Weischedel

  • Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002

    James Allan;Jay Aslam;Nicholas Belkin;Chris Buckley

  • ONTONOTES: A UNIFIED RELATIONAL SEMANTIC REPRESENTATION

    Sameer S. Pradhan;Eduard H. Hovy;Mitchell P. Marcus;Martha Palmer

  • OntoNotes: A Unified Relational Semantic Representation

    a.S. Pradhan;E. Hovy;M.S. Marcus;M. Palmer

  • Meta-rules as a basis for processing ill-formed input

    Ralph M. Weischedel;Norman K. Sondheimer

  • Evaluating a probabilistic model for cross-lingual information retrieval

    Jinxi Xu;Ralph Weischedel;Chanh Nguyen

  • Unrestricted Coreference: Identifying Entities and Events in OntoNotes

    S.S. Pradhan;L. Ramshaw;R. Weischedel;J. MacBride

  • Optimal Network Problem: A Branch-and-Bound Algorithm

    D E Boyce;A Farhi;R Weischedel

  • OntoNotes Release 5.0

    Ralph Weischedel;Martha Palmer;Mitchell Marcus;Eduard Hovy

  • TREC 2003 QA at BBN: Answering Definitional Questions.

    Jinxi Xu;Ana Licuanan;Ralph M. Weischedel

  • BBN: Description of the SIFT System as Used for MUC-7

    Scott Miller;Michael Crystal;Heidi Fox;Lance Ramshaw

  • NAMED ENTITY EXTRACTION FROM SPEECH

    Francis Kubala;Richard Schwartz;Rebecca Stone;Ralph Weischedel

  • Empirical studies in strategies for Arabic retrieval

    Jinxi Xu;Alexander Fraser;Ralph Weischedel

  • Algorithms That Learn to Extract Information BBN: Description of the Sift System as Used for MUC-7

    Scott Miller;Michael Crystal;Heidi Fox;Lance Ramshaw

Frequent Co-Authors

Richard Schwartz
Richard Schwartz Brown University
Nanyun Peng
Nanyun Peng University of California, Los Angeles
Martha Palmer
Martha Palmer University of Colorado Boulder
Aram Galstyan
Aram Galstyan University of Southern California
Eduard Hovy
Eduard Hovy Carnegie Mellon University
Sameer Pradhan
Sameer Pradhan Vassar College
David E. Boyce
David E. Boyce Northwestern University
Aravind K. Joshi
Aravind K. Joshi University of Pennsylvania
Bonnie Webber
Bonnie Webber University of Edinburgh
Nianwen Xue
Nianwen Xue Brandeis University

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