Francesco Piccinno

1.5k total citations
16 papers, 239 citations indexed

About

Francesco Piccinno is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Francesco Piccinno has authored 16 papers receiving a total of 239 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Francesco Piccinno's work include Topic Modeling (11 papers), Natural Language Processing Techniques (11 papers) and Data Quality and Management (2 papers). Francesco Piccinno is often cited by papers focused on Topic Modeling (11 papers), Natural Language Processing Techniques (11 papers) and Data Quality and Management (2 papers). Francesco Piccinno collaborates with scholars based in Italy, United States and Switzerland. Francesco Piccinno's co-authors include Paolo Ferragina, Yasemin Altün, Peter Shaw, Julian Martin Eisenschlos, Roberto Santoro, Fangyu Liu, Nigel Collier, Philip Massey, Chenxi Pang and Kenton Lee and has published in prestigious journals such as Computational Intelligence, Infoscience (Ecole Polytechnique Fédérale de Lausanne) and Cineca Institutional Research Information System (Tor Vergata University).

In The Last Decade

Francesco Piccinno

15 papers receiving 220 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Francesco Piccinno Italy	9	200	47	39	30	14	16	239
Leonhard Hennig Germany	10	250 1.3×	27 0.6×	61 1.6×	11 0.4×	7 0.5×	33	291
Shangwen Lv China	7	285 1.4×	55 1.2×	74 1.9×	17 0.6×	4 0.3×	11	309
Prafulla Kumar Choubey United States	9	276 1.4×	38 0.8×	35 0.9×	44 1.5×	9 0.6×	26	328
Yongbin Liu China	10	203 1.0×	31 0.7×	23 0.6×	29 1.0×	5 0.4×	35	266
Jingyun Xu China	9	302 1.5×	31 0.7×	53 1.4×	46 1.5×	2 0.1×	19	352
Oleksandra Panasiuk Austria	3	95 0.5×	15 0.3×	29 0.7×	39 1.3×	6 0.4×	8	159
Joanna Biega Germany	5	146 0.7×	21 0.4×	30 0.8×	30 1.0×	4 0.3×	5	165
Parth Gupta Spain	10	269 1.3×	41 0.9×	55 1.4×	16 0.5×	9 0.6×	30	320
Diego Ceccarelli Italy	8	169 0.8×	18 0.4×	69 1.8×	47 1.6×	13 0.9×	17	209
Paramita Mirza Germany	10	317 1.6×	17 0.4×	50 1.3×	59 2.0×	5 0.4×	22	335

Countries citing papers authored by Francesco Piccinno

Since Specialization

Citations

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

Fields of papers citing papers by Francesco Piccinno

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Piccinno

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

All Works

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16 of 16 papers shown

Piccinno, Francesco, et al.. (2024). Multimodal Chart Retrieval: A Comparison of Text, Table and Image Based Approaches. 5488–5505. 1 indexed citations

Jain, Parag, et al.. (2024). STRUCTSUM Generation for Faster Text Comprehension. 7876–7896. 1 indexed citations

Pfeiffer, Jonas, et al.. (2023). mmT5: Modular Multilingual Pre-Training Solves Source Language Hallucinations. 1978–2008. 4 indexed citations

Liu, Fangyu, Francesco Piccinno, Chenxi Pang, et al.. (2023). MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering. 12756–12770. 20 indexed citations

Piccinno, Francesco, et al.. (2023). Exploiting Self-Tunable RFID Chips for Wireless Sensing of Permittivity to Enable Passive Low-Cost Food-Quality Monitoring Systems. Cineca Institutional Research Information System (Tor Vergata University). 3 indexed citations

Liu, Fangyu, Julian Martin Eisenschlos, Francesco Piccinno, et al.. (2023). DePlot: One-shot visual language reasoning by plot-to-table translation. 10381–10399. 23 indexed citations

Andrejczuk, Ewa, et al.. (2022). Table-To-Text generation and pre-training with TabT5. 6758–6766. 10 indexed citations

Piccinno, Francesco, et al.. (2022). Byte-Level Massively Multilingual Semantic Parsing. 25–34.

Ferragina, Paolo, Francesco Piccinno, & Roberto Santoro. (2021). On Analyzing Hashtags in Twitter. Proceedings of the International AAAI Conference on Web and Social Media. 9(1). 110–119. 15 indexed citations

10.

Nowak, Paweł Krzysztof, et al.. (2021). Structured Context and High-Coverage Grammar for Conversational Question Answering over Knowledge Graphs. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 12 indexed citations

11.

Piccinno, Francesco, et al.. (2019). Answering Conversational Questions on Structured Data without Logical Forms. 5901–5909. 18 indexed citations

12.

Ferragina, Paolo, et al.. (2019). Swat: A system for detecting salient Wikipedia entities in texts. Computational Intelligence. 35(4). 858–890. 7 indexed citations

13.

Shaw, Peter, et al.. (2019). Generating Logical Forms from Graph Representations of Text and Entities. 95–106. 23 indexed citations

14.

Gupta, Amit, Francesco Piccinno, Mikhail Kozhevnikov, Marius Paşca, & Daniele Pighin. (2016). Revisiting Taxonomy Induction over Wikipedia. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2300–2309. 10 indexed citations

15.

Ferragina, Paolo, Francesco Piccinno, & Rossano Venturini. (2015). Compressed Indexes for String Searching in Labeled Graphs. CINECA IRIS Institutial research information system (University of Pisa). 322–332. 3 indexed citations

16.

Piccinno, Francesco & Paolo Ferragina. (2014). From TagME to WAT. CINECA IRIS Institutial research information system (University of Pisa). 55–62. 89 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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