Francesco Piccinno
Francesco Piccinno
Google DeepMind
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Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
TaPas: Weakly supervised table parsing via pre-training
J Herzig, PK Nowak, T Müller, F Piccinno, JM Eisenschlos
arXiv preprint arXiv:2004.02349, 2020
GERBIL: general entity annotator benchmarking framework
R Usbeck, M Röder, AC Ngonga Ngomo, C Baron, A Both, M Brümmer, ...
Proceedings of the 24th international conference on World Wide Web, 1133-1143, 2015
From TagME to WAT: a new entity annotator
F Piccinno, P Ferragina
Proceedings of the first international workshop on Entity recognition …, 2014
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
On analyzing hashtags in twitter
P Ferragina, F Piccinno, R Santoro
Proceedings of the international AAAI conference on web and social media 9 …, 2015
Deplot: One-shot visual language reasoning by plot-to-table translation
F Liu, JM Eisenschlos, F Piccinno, S Krichene, C Pang, K Lee, M Joshi, ...
arXiv preprint arXiv:2212.10505, 2022
Matcha: Enhancing visual language pretraining with math reasoning and chart derendering
F Liu, F Piccinno, S Krichene, C Pang, K Lee, M Joshi, Y Altun, N Collier, ...
arXiv preprint arXiv:2212.09662, 2022
Generating logical forms from graph representations of text and entities
P Shaw, P Massey, A Chen, F Piccinno, Y Altun
arXiv preprint arXiv:1905.08407, 2019
Answering conversational questions on structured data without logical forms
T Mueller, F Piccinno, M Nicosia, P Shaw, Y Altun
arXiv preprint arXiv:1908.11787, 2019
Swat: A system for detecting salient Wikipedia entities in texts
M Ponza, P Ferragina, F Piccinno
Computational Intelligence 35 (4), 858-890, 2019
Revisiting taxonomy induction over wikipedia
A Gupta, F Piccinno, M Kozhevnikov, M Pasca, D Pighin
Proceedings of COLING 2016, the 26th International Conference on …, 2016
Table-to-text generation and pre-training with tabt5
E Andrejczuk, JM Eisenschlos, F Piccinno, S Krichene, Y Altun
arXiv preprint arXiv:2210.09162, 2022
Structured context and high-coverage grammar for conversational question answering over knowledge graphs
P Marion, PK Nowak, F Piccinno
arXiv preprint arXiv:2109.00269, 2021
mmt5: Modular multilingual pre-training solves source language hallucinations
J Pfeiffer, F Piccinno, M Nicosia, X Wang, M Reid, S Ruder
arXiv preprint arXiv:2305.14224, 2023
Compressed indexes for string searching in labeled graphs
P Ferragina, F Piccinno, R Venturini
Proceedings of the 24th International Conference on World Wide Web, 322-332, 2015
Document aboutness via sophisticated syntactic and semantic features
M Ponza, P Ferragina, F Piccinno
Natural Language Processing and Information Systems: 22nd International …, 2017
Algorithms and data structures for big labeled graphs
F Piccinno
Evaluating byte and wordpiece level models for massively multilingual semantic parsing
M Nicosia, F Piccinno
arXiv preprint arXiv:2212.07223, 2022
What Did You Say? Task-Oriented Dialog Datasets Are Not Conversational!?
AS Jakobovits, F Piccinno, Y Altun
arXiv preprint arXiv:2203.03431, 2022
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