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Found 10 papers, 1 papers with code
BERT 4EVER@LT-EDI-ACL2022-Detecting signs of Depression from Social Media:Detecting Depression in Social Media using Prompt-Learning and Word-Emotion Cluster
In this paper, we report the solution of the team BERT 4EVER for the LT-EDI-2022 shared task2: Homophobia/Transphobia Detection in social media comments in ACL 2022, which aims to classify Youtube comments into one of the following categories: no, moderate, or severe depression.
BERT 4EVER@EvaHan 2022: Ancient Chinese Word Segmentation and Part-of-Speech Tagging Based on Adversarial Learning and Continual Pre-training
In addition, we perform a series of training strategies based on the provided ancient Chinese pre-trained model to enhance the model performance.
Chinese Word Segmentation
Cultural Vocal Bursts Intensity Prediction
+5
How to choose "Good" Samples for Text Data Augmentation
In this paper, we propose a novel self-training selection framework with two selectors to select the high-quality samples from data augmentation.
MIGA: A Unified Multi-task Generation Framework for Conversational Text-to-SQL
Conversational text-to-SQL is designed to translate multi-turn natural language questions into their corresponding SQL queries.
Yunshan Cup 2020: Overview of the Part-of-Speech Tagging Task for Low-resourced Languages
The Yunshan Cup 2020 track focused on creating a framework for evaluating different methods of part-of-speech (POS).
A Dual-Contrastive Framework for Low-Resource Cross-Lingual Named Entity Recognition
In this paper, we describe our novel dual-contrastive framework ConCNER for cross-lingual NER under the scenario of limited source-language labeled data.
CL-XABSA: Contrastive Learning for Cross-lingual Aspect-based Sentiment Analysis
In the distillation XABSA task, we further explore the comparative effectiveness of different data (source dataset, translated dataset, and code-switched dataset).
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+2
LaoPLM: Pre-trained Language Models for Lao
In this work, we construct a text classification dataset to alleviate the resource-scare situation of the Lao language.
An Open-Source Dataset and A Multi-Task Model for Malay Named Entity Recognition
In this work, we propose a dataset construction framework, which is based on labeled datasets of homologous languages and iterative optimization, to build a Malay NER dataset (MYNER) comprising 28, 991 sentences (over 384 thousand tokens).
