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Regression
4,964 papers
Papers per year
2000: 1
2001: 4
2002: 2
2003: 3
2004: 2
2005: 7
2006: 27
2007: 38
2008: 49
2009: 58
2010: 72
2011: 62
2012: 74
2013: 122
2014: 120
2015: 146
2016: 232
2017: 276
2018: 313
2019: 414
2020: 509
2021: 564
2022: 506
2023: 492
2024: 488
2025: 262
2026: 121
Papers
IAPUCP at SemEval-2021 Task 1: Stacking Fine-Tuned Transformers is Almost All You Need for Lexical Complexity Prediction
SEMEVAL 2021
Grenzlinie at SemEval-2021 Task 7: Detecting and Rating Humor and Offense
SEMEVAL 2021
RoMa at SemEval-2021 Task 7: A Transformer-based Approach for Detecting and Rating Humor and Offense
SEMEVAL 2021
SarcasmDet at SemEval-2021 Task 7: Detect Humor and Offensive based on Demographic Factors using RoBERTa Pre-trained Model
SEMEVAL 2021
IITK@LCP at SemEval-2021 Task 1: Classification for Lexical Complexity Regression Task
SEMEVAL 2021
LCP-RIT at SemEval-2021 Task 1: Exploring Linguistic Features for Lexical Complexity Prediction
SEMEVAL 2021
Alejandro Mosquera at SemEval-2021 Task 1: Exploring Sentence and Word Features for Lexical Complexity Prediction
SEMEVAL 2021
CompNA at SemEval-2021 Task 1: Prediction of lexical complexity analyzing heterogeneous features
SEMEVAL 2021
PolyU CBS-Comp at SemEval-2021 Task 1: Lexical Complexity Prediction (LCP)
SEMEVAL 2021
LAST at SemEval-2021 Task 1: Improving Multi-Word Complexity Prediction Using Bigram Association Measures
SEMEVAL 2021
DeepBlueAI at SemEval-2021 Task 1: Lexical Complexity Prediction with A Deep Ensemble Approach
SEMEVAL 2021
CS-UM6P at SemEval-2021 Task 1: A Deep Learning Model-based Pre-trained Transformer Encoder for Lexical Complexity
SEMEVAL 2021
Cambridge at SemEval-2021 Task 1: An Ensemble of Feature-Based and Neural Models for Lexical Complexity Prediction
SEMEVAL 2021
hub at SemEval-2021 Task 1: Fusion of Sentence and Word Frequency to Predict Lexical Complexity
SEMEVAL 2021
Manchester Metropolitan at SemEval-2021 Task 1: Convolutional Networks for Complex Word Identification
SEMEVAL 2021
UPB at SemEval-2021 Task 1: Combining Deep Learning and Hand-Crafted Features for Lexical Complexity Prediction
SEMEVAL 2021
UTFPR at SemEval-2021 Task 1: Complexity Prediction by Combining BERT Vectors and Classic Features
SEMEVAL 2021
RG PA at SemEval-2021 Task 1: A Contextual Attention-based Model with RoBERTa for Lexical Complexity Prediction
SEMEVAL 2021
CSECU-DSG at SemEval-2021 Task 1: Fusion of Transformer Models for Lexical Complexity Prediction
SEMEVAL 2021
CLULEX at SemEval-2021 Task 1: A Simple System Goes a Long Way
SEMEVAL 2021
RS_GV at SemEval-2021 Task 1: Sense Relative Lexical Complexity Prediction
SEMEVAL 2021
UNBNLP at SemEval-2021 Task 1: Predicting lexical complexity with masked language models and character-level encoders
SEMEVAL 2021
JUST-BLUE at SemEval-2021 Task 1: Predicting Lexical Complexity using BERT and RoBERTa Pre-trained Language Models
SEMEVAL 2021
cs60075_team2 at SemEval-2021 Task 1 : Lexical Complexity Prediction using Transformer-based Language Models pre-trained on various text corpora
SEMEVAL 2021
Stanford MLab at SemEval-2021 Task 1: Tree-Based Modelling of Lexical Complexity using Word Embeddings
SEMEVAL 2021
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