Papers Task 2
“Task 2” 태그가 달린 논문 572편 · 필터 해제
No Army, No Navy: BERT Semi-Supervised Learning of Arabic Dialects
We present our deep leaning system submitted to MADAR shared task 2 focused on twitter user dialect identification. We develop tweet-level identification models based on GRUs and BERT in supervised and semi-supervised se…
Dialect IdentificationTask 2Multi-Granularity Fusion Network for Proposal and Activity Localization: Submission to ActivityNet Challenge 2019 Task 1 and Task 2
This technical report presents an overview of our solution used in the submission to ActivityNet Challenge 2019 Task 1 (\textbf{temporal action proposal generation}) and Task 2 (\textbf{temporal action localization/detec…
Action LocalizationDiversityRe-RankingTask 2+2CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology
This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lemma and morpho-syntactic description of e…
LEMMALemmatizationMorphological AnalysisPOS+1Qwant Research @DEFT 2019: Document matching and information retrieval using clinical cases
This paper reports on Qwant Research contribution to tasks 2 and 3 of the DEFT 2019's challenge, focusing on French clinical cases analysis. Task 2 is a task on semantic similarity between clinical cases and discussions.…
Information RetrievalRetrievalSemantic SimilaritySemantic Textual Similarity+1Adversarial Attacks in Sound Event Classification
Adversarial attacks refer to a set of methods that perturb the input to a classification model in order to fool the classifier. In this paper we apply different gradient based adversarial attack algorithms on five deep l…
Adversarial AttackClassificationGeneral ClassificationTask 2Audio tagging with noisy labels and minimal supervision
This paper introduces Task 2 of the DCASE2019 Challenge, titled "Audio tagging with noisy labels and minimal supervision". This task was hosted on the Kaggle platform as "Freesound Audio Tagging 2019". The task evaluates…
Audio TaggingTask 2SemEval-2019 Task 2: Unsupervised Lexical Frame Induction
This paper presents Unsupervised Lexical Frame Induction, Task 2 of the International Workshop on Semantic Evaluation in 2019. Given a set of prespecified syntactic forms in context, the task requires that verbs and thei…
ClusteringTask 2Neural GRANNy at SemEval-2019 Task 2: A combined approach for better modeling of semantic relationships in semantic frame induction
We describe our solutions for semantic frame and role induction subtasks of SemEval 2019 Task 2. Our approaches got the highest scores, and the solution for the frame induction problem officially took the first place. Th…
ClusteringLanguage ModelingLanguage ModellingTask 2L2F/INESC-ID at SemEval-2019 Task 2: Unsupervised Lexical Semantic Frame Induction using Contextualized Word Representations
Building large datasets annotated with semantic information, such as FrameNet, is an expensive process. Consequently, such resources are unavailable for many languages and specific domains. This problem can be alleviated…
ClusteringGraph ClusteringTask 2Word Sense DisambiguationHHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings
We present our system for semantic frame induction that showed the best performance in Subtask B.1 and finished as the runner-up in Subtask A of the SemEval 2019 Task 2 on unsupervised semantic frame induction (QasemiZad…
ClusteringTask 2Word EmbeddingsOvercoming catastrophic forgetting through weight consolidation and long-term memory
Sequential learning of multiple tasks in artificial neural networks using gradient descent leads to catastrophic forgetting, whereby previously learned knowledge is erased during learning of new, disjoint knowledge. Here…
Task 2Facilitating Bayesian Continual Learning by Natural Gradients and Stein Gradients
Continual learning aims to enable machine learning models to learn a general solution space for past and future tasks in a sequential manner. Conventional models tend to forget the knowledge of previous tasks while learn…
Continual LearningTask 2Two Body Problem: Collaborative Visual Task Completion
Collaboration is a necessary skill to perform tasks that are beyond one agent's capabilities. Addressed extensively in both conventional and modern AI, multi-agent collaboration has often been studied in the context of s…
Task 2Vocal Bursts Valence PredictionWord Similarity Datasets for Thai: Construction and Evaluation
Distributional semantics in the form of word embeddings are an essential ingredient to many modern natural language processing systems. The quantification of semantic similarity between words can be used to evaluate the …
Semantic SimilaritySemantic Textual SimilarityTask 2Word Embeddings+1Data Shapley: Equitable Valuation of Data for Machine Learning
As data becomes the fuel driving technological and economic growth, a fundamental challenge is how to quantify the value of data in algorithmic predictions and decisions. For example, in healthcare and consumer markets, …
BIG-bench Machine LearningData ValuationTask 2Human Attention in Image Captioning: Dataset and Analysis
In this work, we present a novel dataset consisting of eye movements and verbal descriptions recorded synchronously over images. Using this data, we study the differences in human attention during free-viewing and image …
Image CaptioningImage DescriptionSentenceTask 2CruzAffect at AffCon 2019 Shared Task: A feature-rich approach to characterize happiness
We present our system, CruzAffect, for the CL-Aff Shared Task 2019. CruzAffect consists of several types of robust and efficient models for affective classification tasks. We utilize both traditional classifiers, such as…
Binary ClassificationClassificationGeneral ClassificationTask 2Combining High-Level Features of Raw Audio Waves and Mel-Spectrograms for Audio Tagging
In this paper, we describe our contribution to Task 2 of the DCASE 2018 Audio Challenge. While it has become ubiquitous to utilize an ensemble of machine learning methods for classification tasks to obtain better predict…
Audio TaggingData AugmentationGeneral ClassificationTask 2General audio tagging with ensembling convolutional neural network and statistical features
Audio tagging aims to infer descriptive labels from audio clips. Audio tagging is challenging due to the limited size of data and noisy labels. In this paper, we describe our solution for the DCASE 2018 Task 2 general au…
Audio TaggingDescriptiveEnsemble LearningTask 2The CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection
The CoNLL--SIGMORPHON 2018 shared task on supervised learning of morphological generation featured data sets from 103 typologically diverse languages. Apart from extending the number of languages involved in earlier supe…
LEMMATask 2