World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
32
Citations
13383
World Ranking
12844
National Ranking
5176

Overview

Julia Hockenmaier is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their body of research primarily lies within the field of Computer Science, with a particular focus on Artificial Intelligence, where they have contributed to 24 publications. Other subfields in which they have conducted research include Computer Vision and Pattern Recognition, Building and Construction, Radiological and Ultrasound Technology, and Management Science and Operations Research.

The main topics addressed in their work cover Natural Language Processing Techniques, represented in 12 publications, as well as Topic Modeling. Other prominent research areas include BIM and Construction Integration, Occupational Health and Safety Research, Speech and Dialogue Systems, Multimodal Machine Learning Applications, and AI-based Problem Solving and Planning.

Julia Hockenmaier's recent papers illustrate their engagement with multiple interrelated research topics. These include:

  • Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models (2024), published in arXiv (Cornell University)
  • Simple Robust Grammar Induction with Combinatory Categorial Grammars (2021), published in Proceedings of the AAAI Conference on Artificial Intelligence
  • Transformer language model for mapping construction schedule activities to uniformat categories (2023), published in Automation in Construction
  • Learning and critiquing pairwise activity relationships for schedule quality control via deep learning-based natural language processing (2021), published in Automation in Construction
  • HySPA: Hybrid Span Generation for Scalable Text-to-Graph Extraction (2021), published in arXiv (Cornell University)

Frequent co-authors collaborating with Julia Hockenmaier include Heng Ji, Yoonhwa Jung, Mani Golparvar-Fard, Liliang Ren, and Rajarshi Haldar.

Their work has been published extensively in venues such as:

  • arXiv (Cornell University), with 14 publications
  • Automation in Construction, with 2 publications
  • Proceedings of the AAAI Conference on Artificial Intelligence, with 1 publication

Best Publications

  • From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions

    Peter Young;Alice Lai;Micah Hodosh;Julia Hockenmaier

  • Framing image description as a ranking task: data, models and evaluation metrics

    Micah Hodosh;Peter Young;Julia Hockenmaier

  • Every picture tells a story: generating sentences from images

    Ali Farhadi;Mohsen Hejrati;Mohammad Amin Sadeghi;Peter Young

  • Framing image description as a ranking task: data, models and evaluation metrics

    Micah Hodosh;Peter Young;Julia Hockenmaier

  • Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models

    Bryan A. Plummer;Liwei Wang;Chris M. Cervantes;Juan C. Caicedo

  • Collecting Image Annotations Using Amazon's Mechanical Turk

    Cyrus Rashtchian;Peter Young;Micah Hodosh;Julia Hockenmaier

  • Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

    Yonatan Bisk;Siva Reddy;John Blitzer;Julia Hockenmaier

  • CCGbank: A Corpus of CCG Derivations and Dependency Structures Extracted from the Penn Treebank

    Julia Hockenmaier;Julia Hockenmaier;Mark Steedman;Mark Steedman

  • Example selection for bootstrapping statistical parsers

    Mark Steedman;Rebecca Hwa;Stephen Clark;Miles Osborne

  • Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models

    Bryan A. Plummer;Liwei Wang;Chris M. Cervantes;Juan C. Caicedo

  • Improving Image-Sentence Embeddings Using Large Weakly Annotated Photo Collections

    Yunchao Gong;Liwei Wang;Micah Hodosh;Julia Hockenmaier

  • Wide-coverage semantic representations from a CCG parser

    Johan Bos;Stephen Clark;Mark Steedman;James R. Curran

  • Data and models for statistical parsing with combinatory categorial grammar

    Julia Hockenmaier

  • Generative Models for Statistical Parsing with Combinatory Categorial Grammar

    Julia Hockenmaier;Mark Steedman

  • Bootstrapping statistical parsers from small datasets

    Mark Steedman;Miles Osborne;Anoop Sarkar;Stephen Clark

  • Phrase Localization and Visual Relationship Detection with Comprehensive Image-Language Cues

    Bryan A. Plummer;Arun Mallya;Christopher M. Cervantes;Julia Hockenmaier

  • Illinois-LH: A Denotational and Distributional Approach to Semantics

    Alice Lai;Julia Hockenmaier

  • Building Deep Dependency Structures using a Wide-Coverage CCG Parser

    Stephen Clark;Julia Hockenmaier;Mark Steedman

  • Identifying semantic roles using Combinatory Categorial Grammar

    Daniel Gildea;Julia Hockenmaier

  • Acquiring Compact Lexicalized Grammars from a Cleaner Treebank.

    Julia Hockenmaier;Mark Steedman

  • Parsing with Generative Models of Predicate-Argument Structure

    Julia Hockenmaier

  • Creating a CCGbank and a Wide-Coverage CCG Lexicon for German

    Julia Hockenmaier

  • Collaborative Dialogue in Minecraft

    Anjali Narayan-Chen;Prashant Jayannavar;Julia Hockenmaier

Frequent Co-Authors

Mark Steedman
Mark Steedman University of Edinburgh
Svetlana Lazebnik
Svetlana Lazebnik University of Illinois at Urbana-Champaign
Aravind K. Joshi
Aravind K. Joshi University of Pennsylvania
Stephen Clark
Stephen Clark Cambridge Quantum Computing
Timothy Baldwin
Timothy Baldwin University of Melbourne
Johan Bos
Johan Bos University of Groningen
Liwei Wang
Liwei Wang Peking University
Gertjan van Noord
Gertjan van Noord University of Groningen
Josef van Genabith
Josef van Genabith Saarland University
James Curran
James Curran University of Sydney

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