Iacer Calixto

1.5k total citations
25 papers, 463 citations indexed

About

Iacer Calixto is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Communication. According to data from OpenAlex, Iacer Calixto has authored 25 papers receiving a total of 463 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 2 papers in Communication. Recurrent topics in Iacer Calixto's work include Natural Language Processing Techniques (20 papers), Topic Modeling (18 papers) and Multimodal Machine Learning Applications (12 papers). Iacer Calixto is often cited by papers focused on Natural Language Processing Techniques (20 papers), Topic Modeling (18 papers) and Multimodal Machine Learning Applications (12 papers). Iacer Calixto collaborates with scholars based in Netherlands, Ireland and United States. Iacer Calixto's co-authors include Qun Liu, Nick Campbell, Andy Way, Sheila Castilho, John Tinsley, Federico Gaspari, Joss Moorkens, Desmond Elliott, Alessandro Raganato and Stella Frank and has published in prestigious journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and Age and Ageing.

In The Last Decade

Iacer Calixto

23 papers receiving 432 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Iacer Calixto Netherlands	11	385	230	42	16	14	25	463
Antonio Valerio Miceli Barone United Kingdom	10	601 1.6×	235 1.0×	17 0.4×	68 4.3×	23 1.6×	22	642
Viresh Ratnakar United States	6	189 0.5×	106 0.5×	7 0.2×	18 1.1×	6 0.4×	14	266
Tanveer J. Siddiqui India	12	248 0.6×	122 0.5×	12 0.3×	41 2.6×	6 0.4×	40	338
Eunah Cho Germany	13	441 1.1×	91 0.4×	10 0.2×	26 1.6×	14 1.0×	41	463
Huda Khayrallah United States	8	263 0.7×	114 0.5×	7 0.2×	17 1.1×	8 0.6×	17	284
Shizhe Diao Hong Kong	9	208 0.5×	75 0.3×	2 0.0×	25 1.6×	14 1.0×	23	280
Nguyễn Bách United States	11	435 1.1×	91 0.4×	6 0.1×	36 2.3×	30 2.1×	31	491
Christian Clausner United Kingdom	15	101 0.3×	442 1.9×	3 0.1×	33 2.1×	4 0.3×	29	514
Junjun Guo China	8	146 0.4×	112 0.5×	5 0.1×	16 1.0×	5 0.4×	45	243
Cheol-Young Ock South Korea	9	219 0.6×	29 0.1×	11 0.3×	55 3.4×	25 1.8×	38	260

Countries citing papers authored by Iacer Calixto

Since Specialization

Citations

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

Fields of papers citing papers by Iacer Calixto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iacer Calixto

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Abu‐Hanna, Ameen, et al.. (2024). Topic evolution before fall incidents in new fallers through natural language processing of general practitioners’ clinical notes. Age and Ageing. 53(2). 3 indexed citations

Zhang, Zeyu, Paul Groth, Iacer Calixto, & Sebastian Schelter. (2024). Directions Towards Efficient and Automated Data Wrangling with Large Language Models. UvA-DARE (University of Amsterdam). 301–304.

Calixto, Iacer, et al.. (2023). LLM aided semi-supervision for efficient Extractive Dialog Summarization. Pure Amsterdam UMC. 10002–10009. 3 indexed citations

Raganato, Alessandro, Iacer Calixto, Asahi Ushio, José Camacho-Collados, & Mohammad Taher Pilehvar. (2023). SemEval-2023 Task 1: Visual Word Sense Disambiguation. BOA (University of Milano-Bicocca). 2227–2234. 25 indexed citations

Dongelmans, Dave A., Iacer Calixto, Ameen Abu‐Hanna, et al.. (2023). Drug-related causes attributed to acute kidney injury and their documentation in intensive care patients. Journal of Critical Care. 75. 154292–154292. 6 indexed citations

Erdem, Aykut, et al.. (2022). Detecting Euphemisms with Literal Descriptions and Visual Imagery. Pure Amsterdam UMC. 61–67. 2 indexed citations

Frank, Anette, et al.. (2022). VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 8253–8280. 26 indexed citations

Frank, Anette, Barbara Plank, Aykut Erdem, et al.. (2022). Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning. Journal of Artificial Intelligence Research. 73. 1131–1207. 26 indexed citations

Calixto, Iacer, Alessandro Raganato, & Tommaso Pasini. (2021). Wikipedia Entities as Rendezvous across Languages: Grounding Multilingual Language Models by Predicting Wikipedia Hyperlinks. UvA-DARE (University of Amsterdam). 3651–3661. 10 indexed citations

10.

Calixto, Iacer & Qun Liu. (2019). An error analysis for image-based multi-modal neural machine translation. Machine Translation. 33(1-2). 155–177. 6 indexed citations

11.

Calixto, Iacer, et al.. (2018). Latent Visual Cues for Neural Machine Translation.. arXiv (Cornell University). 2 indexed citations

12.

Calixto, Iacer, Qun Liu, & Nick Campbell. (2017). Doubly-Attentive Decoder for Multi-modal Neural Machine Translation. 1913–1924. 119 indexed citations

13.

Calixto, Iacer & Qun Liu. (2017). Sentence-Level Multilingual Multi-modal Embedding for Natural Language Processing. 139–148. 8 indexed citations

14.

Calixto, Iacer, D. L. Stein, Evgeny Matusov, Sheila Castilho, & Andy Way. (2017). Human Evaluation of Multi-modal Neural Machine Translation: A Case-Study on E-Commerce Listing Titles. Arrow@dit (Dublin Institute of Technology). 31–37. 7 indexed citations

15.

Calixto, Iacer, et al.. (2017). DCU System Report on the WMT 2017 Multi-modal Machine Translation Task. 440–444. 2 indexed citations

16.

Castilho, Sheila, Joss Moorkens, Federico Gaspari, et al.. (2017). Is Neural Machine Translation the New State of the Art?. SHILAP Revista de lepidopterología. 108(1). 109–120. 117 indexed citations

17.

Ferreira, Thiago Castro, Iacer Calixto, Sander Wubben, & Emiel Krahmer. (2017). Linguistic realisation as machine translation: Comparing different MT models for AMR-to-text generation. Data Archiving and Networked Services (DANS). 1–10. 17 indexed citations

18.

Calixto, Iacer, Desmond Elliott, & Stella Frank. (2016). DCU-UvA Multimodal MT System Report. Edinburgh Research Explorer. 634–638. 24 indexed citations

19.

Štajner, Sanja, Iacer Calixto, & Horacio Saggion. (2015). Automatic text simplification for Spanish: comparative evaluation of various simplification strategies. Recent Advances in Natural Language Processing. 618–626. 20 indexed citations

20.

Ganguly, Debasis, Iacer Calixto, & Gareth J. F. Jones. (2015). Overview of the Automated Story Illustration Task at FIRE 2015.. 63–66. 4 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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