Papers Task 2
“Task 2” 태그가 달린 논문 572편 · 필터 해제
SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC)
In this paper, we introduce the first SemEval task on Multilingual and Cross-Lingual Word-in-Context disambiguation (MCL-WiC). This task allows the largely under-investigated inherent ability of systems to discriminate b…
Binary ClassificationTask 2TA-MAMC at SemEval-2021 Task 4: Task-adaptive Pretraining and Multi-head Attention for Abstract Meaning Reading Comprehension
This paper describes our system used in the SemEval-2021 Task4 Reading Comprehension of Abstract Meaning, achieving 1st for subtask 1 and 2nd for subtask 2 on the leaderboard. We propose an ensemble of ELECTRA-based mode…
Contrastive LearningMultiple-choiceReading ComprehensionTask 2SkoltechNLP at SemEval-2021 Task 2: Generating Cross-Lingual Training Data for the Word-in-Context Task
In this paper, we present a system for the solution of the cross-lingual and multilingual word-in-context disambiguation task. Task organizers provided monolingual data in several languages, but no cross-lingual training…
Language ModelingLanguage ModellingMachine TranslationTask 2+2SzegedAI at SemEval-2021 Task 2: Zero-shot Approach for Multilingual and Cross-lingual Word-in-Context Disambiguation
In this paper, we introduce our system that we participated with at the multilingual and cross-lingual word-in-context disambiguation SemEval 2021 shared task. In our experiments, we investigated the possibility of using…
Task 2Word Sense DisambiguationSarcasmDet at SemEval-2021 Task 7: Detect Humor and Offensive based on Demographic Factors using RoBERTa Pre-trained Model
This paper presents one of the top winning solution systems for task 7 at SemEval2021, HaHackathon: Detecting and Rating Humor and Offense. This competition is divided into two tasks, task1 with three sub-tasks 1a,1b, an…
Task 2IITK@LCP at SemEval-2021 Task 1: Classification for Lexical Complexity Regression Task
This paper describes our contribution to SemEval 2021 Task 1 (Shardlow et al., 2021): Lexical Complexity Prediction. In our approach, we leverage the ELECTRA model and attempt to mirror the data annotation scheme. Althou…
Lexical Complexity PredictionregressionTask 2RG PA at SemEval-2021 Task 1: A Contextual Attention-based Model with RoBERTa for Lexical Complexity Prediction
In this paper we propose a contextual attention based model with two-stage fine-tune training using RoBERTa. First, we perform the first-stage fine-tune on corpus with RoBERTa, so that the model can learn some prior doma…
Lexical Complexity PredictionTask 2cs60075\_team2 at SemEval-2021 Task 1 : Lexical Complexity Prediction using Transformer-based Language Models pre-trained on various text corpora
The main contribution of this paper is to fine-tune transformer-based language models pre-trained on several text corpora, some being general (E.g., Wikipedia, BooksCorpus), some being the corpora from which the CompLex …
Lexical Complexity PredictionTask 2GX at SemEval-2021 Task 2: BERT with Lemma Information for MCL-WiC Task
This paper presents the GX system for the Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) task. The purpose of the MCL-WiC task is to tackle the challenge of capturing the polysemous nature of wor…
LEMMAMachine TranslationTask 2Translation+1hub at SemEval-2021 Task 2: Word Meaning Similarity Prediction Model Based on RoBERTa and Word Frequency
This paper introduces the system description of the hub team, which explains the related work and experimental results of our team{'}s participation in SemEval 2021 Task 2: Multilingual and Cross-lingual Word-in-Context …
Binary ClassificationSentenceTask 2Lotus at SemEval-2021 Task 2: Combination of BERT and Paraphrasing for English Word Sense Disambiguation
In this paper, we describe our proposed methods for the multilingual word-in-Context disambiguation task in SemEval-2021. In this task, systems should determine whether a word that occurs in two different sentences is us…
Task 2Word Sense DisambiguationCambridge at SemEval-2021 Task 2: Neural WiC-Model with Data Augmentation and Exploration of Representation
This paper describes the system of the Cambridge team submitted to the SemEval-2021 shared task on Multilingual and Cross-lingual Word-in-Context Disambiguation. Building on top of a pre-trained masked language model, ou…
Data AugmentationLanguage ModelingLanguage ModellingTask 2UoB\_UK at SemEval 2021 Task 2: Zero-Shot and Few-Shot Learning for Multi-lingual and Cross-lingual Word Sense Disambiguation.
This paper describes our submission to SemEval 2021 Task 2. We compare XLM-RoBERTa Base and Large in the few-shot and zero-shot settings and additionally test the effectiveness of using a k-nearest neighbors classifier i…
Few-Shot LearningTask 2Transfer LearningWord Sense DisambiguationPAW at SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation : Exploring Cross Lingual Transfer, Augmentations and Adversarial Training
We experiment with XLM RoBERTa for Word in Context Disambiguation in the Multi Lingual and Cross Lingual setting so as to develop a single model having knowledge about both settings. We solve the problem as a binary clas…
Binary ClassificationCross-Lingual TransferData AugmentationTask 2GlossReader at SemEval-2021 Task 2: Reading Definitions Improves Contextualized Word Embeddings
Consulting a dictionary or a glossary is a familiar way for many humans to figure out what does a word in a particular context mean. We hypothesize that a system that can select a proper definition for a particular word …
Cross-Lingual TransferLanguage ModellingTask 2Word Embeddings+3UAlberta at SemEval-2021 Task 2: Determining Sense Synonymy via Translations
We describe the University of Alberta systems for the SemEval-2021 Word-in-Context (WiC) disambiguation task. We explore the use of translation information for deciding whether two different tokens of the same word corre…
Explainable ModelsTask 2TranslationLIORI at SemEval-2021 Task 2: Span Prediction and Binary Classification approaches to Word-in-Context Disambiguation
This paper presents our approaches to SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation task. The first approach attempted to reformulate the task as a question answering problem, while t…
Binary ClassificationData AugmentationQuestion AnsweringTask 2+1FII\_CROSS at SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation
This paper presents a word-in-context disambiguation system. The task focuses on capturing the polysemous nature of words in a multilingual and cross-lingual setting, without considering a strict inventory of word meanin…
Task 2Tsia at SemEval-2021 Task 7: Detecting and Rating Humor and Offense
This paper describes our contribution to SemEval-2021 Task 7: Detecting and Rating Humor and Of-fense.This task contains two sub-tasks, sub-task 1and sub-task 2. Among them, sub-task 1 containsthree sub-tasks, sub-task 1…
Task 2Gulu at SemEval-2021 Task 7: Detecting and Rating Humor and Offense
Humor recognition is a challenging task in natural language processing. This document presents my approaches to detect and rate humor and offense from the given text. This task includes 2 tasks: task 1 which contains 3 s…
regressionTask 2