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Computer Science

D-Index
44
Citations
18461
World Ranking
7367
National Ranking
3211

Overview

Mihai Surdeanu is affiliated with the University of Arizona in the United States. Their research primarily focuses on the field of Computer Science, with a strong emphasis on Artificial Intelligence. Additional subfields of study include Information Systems, Management Science and Operations Research, Molecular Biology, and Political Science and International Relations.

The scientist's work covers various topics, including:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Advanced Text Analysis Techniques
  • Expert finding and Q&A systems
  • Text Readability and Simplification
  • Software Engineering Research
  • Semantic Web and Ontologies

Their recent publications cover diverse aspects of natural language processing and related areas. Notable papers include:

  • "Time Travel in LLMs: Tracing Data Contamination in Large Language Models" (2023, arXiv, Cornell University)
  • "Towards the Necessity for Debiasing Natural Language Inference Datasets" (2020, Arabixiv, OSF Preprints)
  • "SuMe: A Dataset Towards Summarizing Biomedical Mechanisms" (2022, UA Campus Repository, The University of Arizona)
  • "Data Contamination Quiz: A Tool to Detect and Estimate Contamination in Large Language Models" (2023, arXiv, Cornell University)
  • "It Takes Two Flints to Make a Fire: Multitask Learning of Neural Relation and Explanation Classifiers" (2022, Computational Linguistics)

Frequent co-authors in their work include:

  • Shahriar Golchin
  • Robert Vacareanu
  • Razvan-Gabriel Dumitru
  • Zheng Tang
  • Zhengzhong Liang

The scientist has published extensively in the following venues:

  • arXiv (Cornell University)
  • UA Campus Repository (The University of Arizona)
  • Arabixiv (OSF Preprints)
  • Computational Linguistics
  • GSA Today

Mihai Surdeanu has authored at least one book, notably published by Cambridge University Press:

  • Deep Learning for Natural Language Processing (2024)

This profile describes a researcher with a broad and detailed engagement in the development of natural language processing methodologies and computational techniques, contributing both scholarly articles and a specialized book to the academic community.

Best Publications

  • The Stanford CoreNLP Natural Language Processing Toolkit

    Christopher Manning;Mihai Surdeanu;John Bauer;Jenny Finkel

  • Multi-instance Multi-label Learning for Relation Extraction

    Mihai Surdeanu;Julie Tibshirani;Ramesh Nallapati;Christopher D. Manning

  • The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages

    Jan Hajiċ;Massimiliano Ciaramita;Richard Johansson;Daisuke Kawahara

  • Stanford’s Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task

    Heeyoung Lee;Yves Peirsman;Angel Chang;Nathanael Chambers

  • The CoNLL 2008 Shared Task on Joint Parsing of Syntactic and Semantic Dependencies

    Mihai Surdeanu;Richard Johansson;Adam Meyers;Lluís Màrquez

  • Deterministic coreference resolution based on entity-centric, precision-ranked rules

    Heeyoung Lee;Angel Chang;Yves Peirsman;Nathanael Chambers

  • Using Predicate-Argument Structures for Information Extraction

    Mihai Surdeanu;Sanda Harabagiu;John Williams;Paul Aarseth

  • Performance issues and error analysis in an open-domain question answering system

    Dan Moldovan;Marius Paşca;Sanda Harabagiu;Mihai Surdeanu

  • A Multi-Pass Sieve for Coreference Resolution

    Karthik Raghunathan;Heeyoung Lee;Sudarshan Rangarajan;Nate Chambers

  • FALCON: Boosting Knowledge for Answer Engines

    Sanda M. Harabagiu;Dan I. Moldovan;Marius. Paşca;Rada Mihalcea

  • Learning to Rank Answers on Large Online QA Collections

    Mihai Surdeanu;Massimiliano Ciaramita;Hugo Zaragoza

  • Joint Entity and Event Coreference Resolution across Documents

    Heeyoung Lee;Marta Recasens;Angel Chang;Mihai Surdeanu

  • Learning to rank answers to non-factoid questions from web collections

    Mihai Surdeanu;Massimiliano Ciaramita;Hugo Zaragoza

  • Event Extraction as Dependency Parsing

    David McClosky;Mihai Surdeanu;Christopher Manning

  • Discourse Complements Lexical Semantics for Non-factoid Answer Reranking

    Peter Jansen;Mihai Surdeanu;Peter Clark

  • The Role of Lexico-Semantic Feedback in Open-Domain Textual Question-Answering

    Sanda Harabagiu;Dan Moldovan;Marius Pasca;Rada Mihalcea

  • Answering complex, list and context questions with LCC's Question-Answering Server

    Sanda M. Harabagiu;Dan I. Moldovan;Marius. Paşca;Mihai Surdeanu

  • On the Importance of Text Analysis for Stock Price Prediction

    Heeyoung Lee;Mihai Surdeanu;Bill MacCartney;Dan Jurafsky

  • Overview of the TAC2013 Knowledge Base Population Evaluation: English Slot Filling and Temporal Slot Filling.

    Mihai Surdeanu

  • Combination strategies for semantic role labeling

    Mihai Surdeanu;Lluís Màrquez;Xavier Carreras;Pere R. Comas

Frequent Co-Authors

Christopher D. Manning
Christopher D. Manning Stanford University
Stephen G. Kobourov
Stephen G. Kobourov University of Arizona
Steven Bethard
Steven Bethard University of Arizona
Dan Moldovan
Dan Moldovan The University of Texas at Dallas
Sanda M. Harabagiu
Sanda M. Harabagiu The University of Texas at Dallas
Lluís Màrquez
Lluís Màrquez Amazon (United States)
Dan Jurafsky
Dan Jurafsky Stanford University
Massimiliano Ciaramita
Massimiliano Ciaramita Google (United States)
Angel X. Chang
Angel X. Chang Simon Fraser University
Eneko Agirre
Eneko Agirre University of the Basque Country

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