Papers Task 2
“Task 2” 태그가 달린 논문 572편 · 필터 해제
Zhegu@SMM4H-2022: The Pre-training Tweet & Claim Matching Makes Your Prediction Better
SMM4H-2022 (CITATION) Task 2 is to detect whether containing premise in the tweets of users about COVID-19 on the social medias or their stances for the claims. In this paper, we propose Tweet Claim Matching (TCM), which…
SentenceTask 2mattica@SMM4H’22: Leveraging sentiment for stance & premise joint learning
This paper describes our submissions to the Social Media Mining for Health Applications (SMM4H) shared task 2022. Our team (mattica) participated in detecting stances and premises in tweets about health mandates related …
Language ModelingLanguage ModellingStance DetectionTask 2Fraunhofer FKIE @ SMM4H 2022: System Description for Shared Tasks 2, 4 and 9
We present our results for the shared tasks 2, 4 and 9 at the SMM4H Workshop at COLING 2022 achieved by succesfully fine-tuning pre-trained language models to the downstream tasks. We identify the occurence of code-switc…
Task 2Innovators@SMM4H’22: An Ensembles Approach for Stance and Premise Classification of COVID-19 Health Mandates Tweets
This paper presents our submission for the Shared Task-2 of classification of stance and premise in tweets about health mandates related to COVID-19 at the Social Media Mining for Health 2022. There have been a plethora …
ClassificationStance DetectionTask 2SMM4H 2022 Task 2: Dataset for stance and premise detection in tweets about health mandates related to COVID-19
This paper is an organizers’ report of the competition on argument mining systems dealing with English tweets about COVID-19 health mandates. This competition was held within the framework of the SMM4H 2022 shared tasks.…
Argument MiningStance DetectionTask 2DAMO-NLP at NLPCC-2022 Task 2: Knowledge Enhanced Robust NER for Speech Entity Linking
Speech Entity Linking aims to recognize and disambiguate named entities in spoken languages. Conventional methods suffer gravely from the unfettered speech styles and the noisy transcripts generated by ASR systems. In th…
Entity Linkingnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+4The SpeakIn Speaker Verification System for Far-Field Speaker Verification Challenge 2022
This paper describes speaker verification (SV) systems submitted by the SpeakIn team to the Task 1 and Task 2 of the Far-Field Speaker Verification Challenge 2022 (FFSVC2022). SV tasks of the challenge focus on the probl…
Speaker VerificationTask 2Transfer LearningApproaching English-Polish Machine Translation Quality Assessment with Neural-based Methods
This paper presents our contribution to the PolEval 2021 Task 2: Evaluation of translation quality assessment metrics. We describe experiments with pre-trained language models and state-of-the-art frameworks for translat…
Machine TranslationTask 2TranslationDetecting Political Biases of Named Entities and Hashtags on Twitter
Ideological divisions in the United States have become increasingly prominent in daily communication. Accordingly, there has been much research on political polarization, including many recent efforts that take a computa…
Multi-Task LearningTask 2Extending nnU-Net is all you need
Semantic segmentation is one of the most popular research areas in medical image computing. Perhaps surprisingly, despite its conceptualization dating back to 2018, nnU-Net continues to provide competitive out-of-the-box…
AllSegmentationSemantic SegmentationTask 2Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021
Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating…
DiagnosticTask 2Instance Image Retrieval by Learning Purely From Within the Dataset
Quality feature representation is key to instance image retrieval. To attain it, existing methods usually resort to a deep model pre-trained on benchmark datasets or even fine-tune the model with a task-dependent labelle…
Image RetrievalRetrievalSelf-Supervised LearningTask 2A Semantic Alignment System for Multilingual Query-Product Retrieval
This paper mainly describes our winning solution (team name: www) to Amazon ESCI Challenge of KDD CUP 2022, which achieves a NDCG score of 0.9043 and wins the first place on task 1: the query-product ranking track. In th…
Data AugmentationRetrievalTask 2DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation
Unsupervised domain adaptation in semantic segmentation has been raised to alleviate the reliance on expensive pixel-wise annotations. It leverages a labeled source domain dataset as well as unlabeled target domain image…
Domain AdaptationSegmentationSemantic SegmentationTask 2+1Boosting Multi-Modal E-commerce Attribute Value Extraction via Unified Learning Scheme and Dynamic Range Minimization
With the prosperity of e-commerce industry, various modalities, e.g., vision and language, are utilized to describe product items. It is an enormous challenge to understand such diversified data, especially via extractin…
AttributeAttribute Value ExtractionDescriptiveTask 2Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting
In multi-modal multi-agent trajectory forecasting, two major challenges have not been fully tackled: 1) how to measure the uncertainty brought by the interaction module that causes correlations among the predicted trajec…
regressionTask 2Trajectory ForecastingContinual Few-Shot Learning with Adversarial Class Storage
Humans have a remarkable ability to quickly and effectively learn new concepts in a continuous manner without forgetting old knowledge. Though deep learning has made tremendous successes on various computer vision tasks,…
continual few-shot learningFew-Shot LearningMeta-LearningTask 2HeiMorph at SIGMORPHON 2022 Shared Task on Morphological Acquisition Trajectories
This paper presents the submission by the HeiMorph team to the SIGMORPHON 2022 task 2 of Morphological Acquisition Trajectories. Across all experimental conditions, we have found no evidence for the so-called Ushaped dev…
HallucinationTask 2Helsinki-NLP at SemEval-2022 Task 2: A Feature-Based Approach to Multilingual Idiomaticity Detection
This paper describes the University of Helsinki submission to the SemEval 2022 task on multilingual idiomaticity detection. Our system utilizes several models made available by HuggingFace, along with the baseline BERT m…
Feature EngineeringTask 2Hitachi at SemEval-2022 Task 2: On the Effectiveness of Span-based Classification Approaches for Multilingual Idiomaticity Detection
In this paper, we describe our system for SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding. The task aims at detecting idiomaticity in an input sequence (Subtask A) and modeling representat…
ClassificationSentenceSentence EmbeddingSentence-Embedding+2