Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
The Proposition Bank: An Annotated Corpus of Semantic Roles
This map shows the geographic impact of Daniel Gildea's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Gildea with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Gildea more than expected).
This network shows the impact of papers produced by Daniel Gildea. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Gildea. The network helps show where Daniel Gildea may publish in the future.
Co-authorship network of co-authors of Daniel Gildea
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Gildea.
A scholar is included among the top collaborators of Daniel Gildea based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Daniel Gildea. Daniel Gildea is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ding, Chen, et al.. (2018). All timescale window co-occurrence: efficient analysis and a possible use.. Conference of the Centre for Advanced Studies on Collaborative Research. 289–292.1 indexed citations
3.
Gildea, Daniel, et al.. (2013). Plurality, Negation, and Quantification:Towards Comprehensive Quantifier Scope Disambiguation. Meeting of the Association for Computational Linguistics. 1. 64–72.4 indexed citations
4.
Naim, Iftekhar, Daniel Gildea, Walter S. Lasecki, & Jeffrey P. Bigham. (2013). Text Alignment for Real-Time Crowd Captioning. North American Chapter of the Association for Computational Linguistics. 201–210.17 indexed citations
5.
Gildea, Daniel, et al.. (2012). Improving the IBM Alignment Models Using Variational Bayes. Meeting of the Association for Computational Linguistics. 306–310.14 indexed citations
6.
Chung, Tagyoung, et al.. (2011). Terminal-Aware Synchronous Binarization. Meeting of the Association for Computational Linguistics. 401–406.3 indexed citations
7.
Chung, Tagyoung, et al.. (2011). Issues Concerning Decoding with Synchronous Context-free Grammar. Meeting of the Association for Computational Linguistics. 413–417.10 indexed citations
8.
Liu, Ding & Daniel Gildea. (2010). Semantic Role Features for Machine Translation. International Conference on Computational Linguistics. 716–724.61 indexed citations
9.
Gildea, Daniel. (2010). Optimal Parsing Strategies for Linear Context-Free Rewriting Systems. UR Research (University of Rochester). 769–776.18 indexed citations
10.
Post, Matt & Daniel Gildea. (2008). Parsers as language models for statistical machine translation. Conference of the Association for Machine Translation in the Americas. 172–181.18 indexed citations
11.
Zhang, Hao, Chris Quirk, Robert C. Moore, & Daniel Gildea. (2008). Bayesian Learning of Non-Compositional Phrases with Synchronous Parsing. Meeting of the Association for Computational Linguistics. 97–105.49 indexed citations
12.
Zhang, Hao & Daniel Gildea. (2008). Efficient Multi-Pass Decoding for Synchronous Context Free Grammars. Meeting of the Association for Computational Linguistics. 209–217.21 indexed citations
13.
Zhang, Hao & Daniel Gildea. (2007). Enumeration of Factorizable Multi-Dimensional Permutations. Journal of integer sequences. 10(5). 58.2 indexed citations
14.
Liu, Ding & Daniel Gildea. (2007). Source-Language Features and Maximum Correlation Training for Machine Translation Evaluation. North American Chapter of the Association for Computational Linguistics. 41–48.18 indexed citations
15.
Gildea, Daniel & David Temperley. (2007). Optimizing Grammars for Minimum Dependency Length. Meeting of the Association for Computational Linguistics. 184–191.27 indexed citations
16.
Gildea, Daniel & Daniel Štefankovič. (2007). Worst-Case Synchronous Grammar Rules. North American Chapter of the Association for Computational Linguistics. 147–154.8 indexed citations
17.
Liu, Ding & Daniel Gildea. (2005). Syntactic Features for Evaluation of Machine Translation. Meeting of the Association for Computational Linguistics. 25–32.113 indexed citations
18.
Gildea, Daniel. (2004). Dependencies vs. Constituents for Tree-Based Alignment. Empirical Methods in Natural Language Processing. 214–221.14 indexed citations
19.
Gildea, Daniel & Daniel Jurafsky. (2003). Identifying semantic relations in text. Morgan Kaufmann Publishers Inc. eBooks. 69–102.
20.
Gildea, Daniel. (2001). Corpus Variation and Parser Performance. Empirical Methods in Natural Language Processing.189 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.