statistiche ricercatore

Continente	#
EU - Europa	977
NA - Nord America	635
AS - Asia	331
SA - Sud America	36
AF - Africa	7
OC - Oceania	2
Continente sconosciuto - Info sul continente non disponibili	1
Totale	1.989

Nazione	#
US - Stati Uniti d'America	590
IT - Italia	212
DE - Germania	208
IE - Irlanda	177
RU - Federazione Russa	129
CN - Cina	94
SG - Singapore	88
GB - Regno Unito	80
FR - Francia	53
CA - Canada	36
HK - Hong Kong	33
UA - Ucraina	31
BR - Brasile	30
SE - Svezia	24
FI - Finlandia	21
VN - Vietnam	20
IL - Israele	19
TR - Turchia	19
ID - Indonesia	16
IN - India	16
CZ - Repubblica Ceca	11
JP - Giappone	8
RO - Romania	6
MX - Messico	5
PL - Polonia	5
BE - Belgio	4
HU - Ungheria	4
CO - Colombia	3
IR - Iran	3
MA - Marocco	3
PA - Panama	3
TH - Thailandia	3
AT - Austria	2
AU - Australia	2
BD - Bangladesh	2
EE - Estonia	2
KG - Kirghizistan	2
NL - Olanda	2
PE - Perù	2
PK - Pakistan	2
SC - Seychelles	2
AZ - Azerbaigian	1
BO - Bolivia	1
CH - Svizzera	1
EG - Egitto	1
ES - Italia	1
EU - Europa	1
GR - Grecia	1
KR - Corea	1
LB - Libano	1
LT - Lituania	1
NI - Nicaragua	1
NO - Norvegia	1
OM - Oman	1
PH - Filippine	1
SA - Arabia Saudita	1
SK - Slovacchia (Repubblica Slovacca)	1
ZA - Sudafrica	1
Totale	1.989

Nome	#
Geolocation with attention-based multitask learning models	204
Dense node representation for geolocation	195
Identifying linguistic areas for geolocation	190
Increasing in-class similarity by retrofitting embeddings with demographic information	182
Helpful or hierarchical? Predicting the communicative strategies of chat participants, and their impact on success	168
A case for soft loss functions	126
Fake opinion detection: how similar are crowdsourced datasets to real data?	102
MilaNLP @ WASSA: does BERT feel sad when you cry?	102
“You sound just like your father”. Commercial machine translation systems include stylistic biases	98
BERTective: language models and contextual information for deception detection	98
Gender and age bias in commercial machine translation	84
Beyond black & white: leveraging annotator disagreement via soft-label multi-task learning	80
“We will reduce taxes” - Identifying election pledges with language models	77
ProSiT! Latent Variable Discovery with PROgressive SImilarity Thresholds	72
Hard and soft evaluation of NLP models with BOOtSTrap SAmpling - BooStSa	71
We need to consider disagreement in evaluation	71
SemEval-2021 Task 12: learning with disagreements	67
Learning from disagreement: a survey	61
Totale	2.048

	Totale	Lug	Ago	Sett	Ott	Nov	Dic	Gen	Feb	Mar	Apr	Mag	Giu
2019/2020	13	0	0	0	0	0	0	0	0	0	0	0	13
2020/2021	199	5	5	4	11	24	11	40	24	19	23	12	21
2021/2022	264	22	79	3	9	40	15	13	26	8	14	14	21
2022/2023	600	48	45	47	70	50	37	7	22	223	25	20	6
2023/2024	391	18	27	35	18	43	61	27	31	7	14	45	65
2024/2025	529	13	15	43	12	33	22	69	28	150	60	63	21
Totale													2.048