This map shows the geographic impact of Anton Leuski'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 Anton Leuski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anton Leuski more than expected).
This network shows the impact of papers produced by Anton Leuski. 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 Anton Leuski. The network helps show where Anton Leuski may publish in the future.
Co-authorship network of co-authors of Anton Leuski
This figure shows the co-authorship network connecting the top 25 collaborators of Anton Leuski.
A scholar is included among the top collaborators of Anton Leuski 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 Anton Leuski. Anton Leuski is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Georgila, Kallirroi, et al.. (2020). Evaluation of Off-the-shelf Speech Recognizers Across Diverse Dialogue Domains. Language Resources and Evaluation. 6469–6476.5 indexed citations
3.
Leuski, Anton, et al.. (2020). Which Model Should We Use for a Real-World Conversational Dialogue System? a Cross-Language Relevance Model or a Deep Neural Net?. Language Resources and Evaluation. 735–742.1 indexed citations
4.
Leuski, Anton, et al.. (2019). PRIMER: An Emotionally Aware Virtual Agent..4 indexed citations
5.
Artstein, Ron, Jill Boberg, Alesia Gainer, et al.. (2018). The Niki and Julie Corpus: Collaborative Multimodal Dialogues between Humans, Robots, and Virtual Agents. Language Resources and Evaluation.3 indexed citations
Artstein, Ron, David Traum, Jill Boberg, et al.. (2017). Listen to My Body: Does Making Friends Help Influence People?. The Florida AI Research Society. 430–435.8 indexed citations
8.
Artstein, Ron, et al.. (2015). How Many Utterances Are Needed to Support Time-Offset Interaction?. The Florida AI Research Society. 144–149.7 indexed citations
Morbini, Fabrizio, Kartik Audhkhasi, Kenji Sagae, et al.. (2013). Which ASR should I choose for my dialogue system. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 394–403.26 indexed citations
11.
Misu, Teruhisa, Kallirroi Georgila, Anton Leuski, & David Traum. (2012). Reinforcement Learning of Question-Answering Dialogue Policies for Virtual Museum Guides. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 84–93.25 indexed citations
12.
Chen, Grace, et al.. (2011). Evaluating Conversational Characters Created through Question Generation.. The Florida AI Research Society.4 indexed citations
13.
DeVault, David, Anton Leuski, & Kenji Sagae. (2011). An Evaluation of Alternative Strategies for Implementing Dialogue Policies Using Statistical Classification and Rules. International Joint Conference on Natural Language Processing.4 indexed citations
14.
Leuski, Anton & David Traum. (2010). NPCEditor: A Tool for Building Question-Answering Characters.. Language Resources and Evaluation.15 indexed citations
15.
Artstein, Ron, et al.. (2008). Field Testing of an Interactive Question-Answering Character. Language Resources and Evaluation.8 indexed citations
16.
Traum, David, Anton Leuski, Antônio C. Roque, et al.. (2008). Natural Language Dialogue Architectures for Tactical Questioning Characters.11 indexed citations
17.
Martinovski, Bilyana, David Traum, Antônio C. Roque, et al.. (2007). A Virtual Human for Tactical Questioning. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 24(10). 477–484.3 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.