Papers Task 2
“Task 2” 태그가 달린 논문 572편 · 필터 해제
DeepBlueAI at WANLP-EACL2021 task 2: A Deep Ensemble-based Method for Sarcasm and Sentiment Detection in Arabic
Sarcasm is one of the main challenges for sentiment analysis systems due to using implicit indirect phrasing for expressing opinions, especially in Arabic. This paper presents the system we submitted to the Sarcasm and S…
Sentiment AnalysisTask 2IA-GCN: Interpretable Attention based Graph Convolutional Network for Disease prediction
Interpretability in Graph Convolutional Networks (GCNs) has been explored to some extent in computer vision in general, yet, in the medical domain, it requires further examination. Moreover, most of the interpretability …
Decision MakingDisease PredictionGender PredictionGraph Learning+1ICDAR2019 Competition on Scanned Receipt OCR and Information Extraction
Scanned receipts OCR and key information extraction (SROIE) represent the processeses of recognizing text from scanned receipts and extracting key texts from them and save the extracted tests to structured documents. SRO…
Key Information ExtractionOptical Character Recognition (OCR)Task 2AraBERT and Farasa Segmentation Based Approach For Sarcasm and Sentiment Detection in Arabic Tweets
This paper presents our strategy to tackle the EACL WANLP-2021 Shared Task 2: Sarcasm and Sentiment Detection. One of the subtasks aims at developing a system that identifies whether a given Arabic tweet is sarcastic in …
Task 2BERT-based Acronym Disambiguation with Multiple Training Strategies
Acronym disambiguation (AD) task aims to find the correct expansions of an ambiguous ancronym in a given sentence. Although it is convenient to use acronyms, sometimes they could be difficult to understand. Identifying t…
Binary ClassificationSentenceTask 2KBCNMUJAL@HASOC-Dravidian-CodeMix-FIRE2020: Using Machine Learning for Detection of Hate Speech and Offensive Code-Mixed Social Media text
This paper describes the system submitted by our team, KBCNMUJAL, for Task 2 of the shared task Hate Speech and Offensive Content Identification in Indo-European Languages (HASOC), at Forum for Information Retrieval Eval…
Information RetrievalRetrievalTask 2A Survey and Analysis on Automated Glioma Brain Tumor Segmentation and Overall Patient Survival Prediction
Glioma is the most deadly brain tumor with high mortality. Treatment planning by human experts depends on the proper diagnosis of physical symptoms along with Magnetic Resonance(MR) image analysis. Highly variability of …
Brain Tumor SegmentationSegmentationSurvival PredictionTask 2+1Unsupervised Technical Domain Terms Extraction using Term Extractor
Terminology extraction, also known as term extraction, is a subtask of information extraction. The goal of terminology extraction is to extract relevant words or phrases from a given corpus automatically. This paper focu…
ChunkingTask 2Term ExtractionWeChat AI & ICT's Submission for DSTC9 Interactive Dialogue Evaluation Track
We participate in the DSTC9 Interactive Dialogue Evaluation Track (Gunasekara et al. 2020) sub-task 1 (Knowledge Grounded Dialogue) and sub-task 2 (Interactive Dialogue). In sub-task 1, we employ a pre-trained language m…
Dialogue EvaluationLanguage ModelingLanguage ModellingTask 2Hand Pose Estimation in the Task of Egocentric Actions
In this article we tackle the problem of hand pose estimation when the hand is interacting with various objects from egocentric viewpoint. This entails a frequent occlusion of parts of the hand by the object and also sel…
3D Hand Pose EstimationHand Pose EstimationPose EstimationTask 2Iterative weak/self-supervised classification framework for abnormal events detection
The detection of abnormal events in surveillance footage remains a challenge and has been the scope of various research works. Having observed that the state-of-the-art performance is still unsatisfactory, this paper pro…
Abnormal Event Detection In VideoAnomaly DetectionAnomaly Detection In Surveillance VideosClassification+7IEPT: Instance-Level and Episode-Level Pretext Tasks for Few-Shot Learning
The need of collecting large quantities of labeled training data for each new task has limited the usefulness of deep neural networks. Given data from a set of source tasks, this limitation can be overcome using two tran…
Few-Shot LearningMeta-LearningSelf-Supervised LearningTask 2+1THUIR@COLIEE-2020: Leveraging Semantic Understanding and Exact Matching for Legal Case Retrieval and Entailment
In this paper, we present our methodologies for tackling the challenges of legal case retrieval and entailment in the Competition on Legal Information Extraction / Entailment 2020 (COLIEE-2020). We participated in the tw…
RetrievalTask 2Seeing past words: Testing the cross-modal capabilities of pretrained V&L models on counting tasks
We investigate the reasoning ability of pretrained vision and language (V&L) models in two tasks that require multimodal integration: (1) discriminating a correct image-sentence pair from an incorrect one, and (2) counti…
SentenceTask 2Dartmouth CS at WNUT-2020 Task 2: Informative COVID-19 Tweet Classification Using BERT
We describe the systems developed for the WNUT-2020 shared task 2, identification of informative COVID-19 English Tweets. BERT is a highly performant model for Natural Language Processing tasks. We increased BERT's perfo…
General ClassificationTask 2Enhanced Offensive Language Detection Through Data Augmentation
Detecting offensive language on social media is an important task. The ICWSM-2020 Data Challenge Task 2 is aimed at identifying offensive content using a crowd-sourced dataset containing 100k labelled tweets. The dataset…
Data AugmentationTask 2Financial Document Causality Detection Shared Task (FinCausal 2020)
We present the FinCausal 2020 Shared Task on Causality Detection in Financial Documents and the associated FinCausal dataset, and discuss the participating systems and results. Two sub-tasks are proposed: a binary classi…
Binary ClassificationRelation ExtractionTask 2SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment
Lexical entailment (LE) is a fundamental asymmetric lexico-semantic relation, supporting the hierarchies in lexical resources (e.g., WordNet, ConceptNet) and applications like natural language inference and taxonomy indu…
Lexical EntailmentNatural Language InferenceTask 2BMEAUT at SemEval-2020 Task 2: Lexical Entailment with Semantic Graphs
In this paper we present a novel rule-based, language independent method for determining lexical entailment relations using semantic representations built from Wiktionary definitions. Combined with a simple WordNet-based…
Lexical EntailmentSemantic ParsingTask 2SHIKEBLCU at SemEval-2020 Task 2: An External Knowledge-enhanced Matrix for Multilingual and Cross-Lingual Lexical Entailment
Lexical entailment recognition plays an important role in tasks like Question Answering and Machine Translation. As important branches of lexical entailment, predicting multilingual and cross-lingual lexical entailment (…
Lexical EntailmentMachine TranslationMultilingual Word EmbeddingsQuestion Answering+3