David Schlangen

3.4k total citations
145 papers, 1.5k citations indexed

About

David Schlangen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Language and Linguistics. According to data from OpenAlex, David Schlangen has authored 145 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 126 papers in Artificial Intelligence, 34 papers in Computer Vision and Pattern Recognition and 22 papers in Language and Linguistics. Recurrent topics in David Schlangen's work include Speech and dialogue systems (98 papers), Natural Language Processing Techniques (58 papers) and Topic Modeling (56 papers). David Schlangen is often cited by papers focused on Speech and dialogue systems (98 papers), Natural Language Processing Techniques (58 papers) and Topic Modeling (56 papers). David Schlangen collaborates with scholars based in Germany, United States and Sweden. David Schlangen's co-authors include Timo Baumann, Gabriel Skantze, Casey Kennington, Julian Hough, Michaela Atterer, Sina Zarrieß, Raquel Fernández, Stefan Kopp, Hendrik Buschmeier and Alex Lascarides and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Vision and Language Resources and Evaluation.

In The Last Decade

David Schlangen

136 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Schlangen Germany 20 1.3k 275 232 217 213 145 1.5k
Amy Isard United Kingdom 14 679 0.5× 176 0.6× 83 0.4× 89 0.4× 115 0.5× 48 864
Catharine Oertel Sweden 15 323 0.2× 281 1.0× 96 0.4× 64 0.3× 140 0.7× 51 593
Antoine Raux United States 18 1.2k 0.9× 155 0.6× 137 0.6× 90 0.4× 101 0.5× 46 1.3k
Scott Prevost United States 9 339 0.3× 216 0.8× 214 0.9× 68 0.3× 133 0.6× 13 675
Mikio Nakano Japan 17 636 0.5× 291 1.1× 143 0.6× 29 0.1× 73 0.3× 120 964
Samer Al Moubayed Sweden 12 220 0.2× 218 0.8× 147 0.6× 34 0.2× 86 0.4× 49 497
Rolf Carlson Sweden 17 598 0.5× 76 0.3× 78 0.3× 79 0.4× 397 1.9× 97 864
Masafumi Nishida Japan 10 203 0.2× 85 0.3× 78 0.3× 85 0.4× 73 0.3× 57 380
William Schuler United States 19 697 0.5× 64 0.2× 87 0.4× 81 0.4× 60 0.3× 86 1.1k
Piero Cosi Italy 14 343 0.3× 113 0.4× 155 0.7× 21 0.1× 158 0.7× 75 615

Countries citing papers authored by David Schlangen

Since Specialization
Citations

This map shows the geographic impact of David Schlangen'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 David Schlangen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Schlangen more than expected).

Fields of papers citing papers by David Schlangen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Schlangen. 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 David Schlangen. The network helps show where David Schlangen may publish in the future.

Co-authorship network of co-authors of David Schlangen

This figure shows the co-authorship network connecting the top 25 collaborators of David Schlangen. A scholar is included among the top collaborators of David Schlangen 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 David Schlangen. David Schlangen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Schlangen, David. (2023). On General Language Understanding. 8818–8825. 1 indexed citations
3.
Schlangen, David, et al.. (2023). clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents. 11174–11219. 4 indexed citations
5.
Schlangen, David, et al.. (2018). A Corpus of Natural Multimodal Spatial Scene Descriptions. Language Resources and Evaluation. 1 indexed citations
6.
Kennington, Casey, et al.. (2015). A Discriminative Model for Perceptually-Grounded Incremental Reference Resolution. PUB – Publications at Bielefeld University (Bielefeld University). 16(1). 195–205. 8 indexed citations
7.
Schlangen, David, et al.. (2015). The Power of a Glance: Evaluating Embodiment and Turn-Tracking Strategies of an Active Robotic Overhearer. PUB – Publications at Bielefeld University (Bielefeld University). 43. 3 indexed citations
8.
Schlangen, David, et al.. (2014). Towards Closed Feedback Loops in HRI. PUB – Publications at Bielefeld University (Bielefeld University). 2 indexed citations
9.
Kennington, Casey, et al.. (2014). Situated Incremental Natural Language Understanding using a Multimodal, Linguistically-driven Update Model. Publikationen an der Universität Bielefeld (Universität Bielefeld). 1803–1812. 4 indexed citations
10.
Kennington, Casey, et al.. (2013). Investigating speaker gaze and pointing behaviour in human-computer interaction with the mint.tools collection. PUB – Publications at Bielefeld University (Bielefeld University). 319–323. 8 indexed citations
11.
Peldszus, Andreas, et al.. (2012). Joint Satisfaction of Syntactic and Pragmatic Constraints Improves Incremental Spoken Language Understanding. PUB – Publications at Bielefeld University (Bielefeld University). 514–523. 13 indexed citations
12.
Pfeiffer, Thies, et al.. (2012). Evaluating a minimally invasive laboratory architecture for recording multimodal conversational data. PUB – Publications at Bielefeld University (Bielefeld University). 42. 15 indexed citations
13.
Peldszus, Andreas & David Schlangen. (2012). Incremental Construction of Robust but Deep Semantic Representations for Use in Responsive Dialogue Systems. International Conference on Computational Linguistics. 20(5). 59–76. 3 indexed citations
14.
Baumann, Timo & David Schlangen. (2012). INPRO_iSS: A Component for Just-In-Time Incremental Speech Synthesis. PUB – Publications at Bielefeld University (Bielefeld University). 103–108. 27 indexed citations
15.
Kennington, Casey & David Schlangen. (2012). Markov Logic Networks for Situated Incremental Natural Language Understanding. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 314–323. 10 indexed citations
16.
Baumann, Timo & David Schlangen. (2012). The InproTK 2012 release. PUB – Publications at Bielefeld University (Bielefeld University). 29–32. 39 indexed citations
17.
Fernández, Raquel, Staffan Larsson, Robin Cooper, Jonathan Ginzburg, & David Schlangen. (2011). Reciprocal Learning via Dialogue Interaction: Challenges and Prospects. UvA-DARE (University of Amsterdam). 7 indexed citations
18.
Baumann, Timo, et al.. (2010). Comparing Local and Sequential Models for Statistical Incremental Natural Language Understanding. Publikationen an der Universität Bielefeld (Universität Bielefeld). 9–16. 22 indexed citations
19.
Schlangen, David, Timo Baumann, Hendrik Buschmeier, et al.. (2010). Middleware for Incremental Processing in Conversational Agents. PUB – Publications at Bielefeld University (Bielefeld University). 51–54. 21 indexed citations
20.
Schlangen, David & Alex Lascarides. (2003). The interpretation of non-sentential utterances in dialogue. Publikationen an der Universität Bielefeld (Universität Bielefeld). 62–71. 14 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.

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