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Found 17 papers, 3 papers with code
Learning Cross-lingual Representations for Event Coreference Resolution with Multi-view Alignment and Optimal Transport
We study a new problem of cross-lingual transfer learning for event coreference resolution (ECR) where models trained on data from a source language are adapted for evaluations in different target languages.
Improving Cross-Lingual Transfer for Event Argument Extraction with Language-Universal Sentence Structures
Previous work on CEAE has shown the cross-lingual benefits of universal dependency trees in capturing shared syntactic structures of sentences across languages.
Joint Extraction of Entities, Relations, and Events via Modeling Inter-Instance and Inter-Label Dependencies
However, previous JointIE models often assume heuristic manually-designed dependency between the task instances and mean-field factorization for the joint distribution of instance labels, thus unable to capture optimal dependencies among instances and labels to improve representation learning and IE performance.
Cross-Lingual Event Detection via Optimized Adversarial Training
In this work, we focus on Cross-Lingual Event Detection where a model is trained on data from a \textit{source} language but its performance is evaluated on data from a second, \textit{target}, language.
MECI: A Multilingual Dataset for Event Causality Identification
Our dataset thus enable a new research direction on cross-lingual transfer learning for ECI.
Crosslingual Transfer Learning for Relation and Event Extraction via Word Category and Class Alignments
To address this issue, we propose a novel crosslingual alignment method that leverages class information of REE tasks for representation learning.
Document-Level Event Argument Extraction via Optimal Transport
Event Argument Extraction (EAE) is one of the sub-tasks of event extraction, aiming to recognize the role of each entity mention toward a specific event trigger.
BehanceMT: A Machine Translation Corpus for Livestreaming Video Transcripts
As a result, such MT systems could fail to translate livestreaming video transcripts, where text is often shorter and might be grammatically incorrect.
Modeling Document-Level Context for Event Detection via Important Context Selection
To address this issue, we propose a novel method to model document-level context for ED that dynamically selects relevant sentences in the document for the event prediction of the target sentence.
Fine-grained Temporal Relation Extraction with Ordered-Neuron LSTM and Graph Convolutional Networks
In this work, we propose to fill this gap by introducing novel methods to integrate the syntactic structures into the deep learning models for FineTempRel.
Question-Context Alignment and Answer-Context Dependencies for Effective Answer Sentence Selection
In this paper, we propose to improve the candidate scoring by explicitly incorporating the dependencies between question-context and answer-context into the final representation of a candidate.
MINION: a Large-Scale and Diverse Dataset for Multilingual Event Detection
Event Detection (ED) is the task of identifying and classifying trigger words of event mentions in text.
FAMIE: A Fast Active Learning Framework for Multilingual Information Extraction
FAMIE is designed to address a fundamental problem in existing AL frameworks where annotators need to wait for a long time between annotation batches due to the time-consuming nature of model training and data selection at each AL iteration.
Custom Deep Neural Network for 3D Covid Chest CT-scan Classification
3D CT-scan base on chest is one of the controversial topisc of the researcher nowadays.
Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks
Existing works on information extraction (IE) have mainly solved the four main tasks separately (entity mention recognition, relation extraction, event trigger detection, and argument extraction), thus failing to benefit from inter-dependencies between tasks.
Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing
Finally, we create a demo video for Trankit at: https://youtu. be/q0KGP3zGjGc.
Ranked #1 on
Sentence segmentation
on UD2.5 test
