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Found 11 papers, 2 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.
GAgent: An Adaptive Rigid-Soft Gripping Agent with Vision Language Models for Complex Lighting Environments
This paper introduces GAgent: an Gripping Agent designed for open-world environments that provides advanced cognitive abilities via VLM agents and flexible grasping abilities with variable stiffness soft grippers.
Characterising User Transfer Amid Industrial Resource Variation: A Bayesian Nonparametric Approach
In a multitude of industrial fields, a key objective entails optimising resource management whilst satisfying user requirements.
A Survey on Deep Multi-modal Learning for Body Language Recognition and Generation
In summary, this survey paper provides a comprehensive understanding of deep multi-modal learning for various BL generations and recognitions for the first time.
Mitigating Catastrophic Forgetting in Task-Incremental Continual Learning with Adaptive Classification Criterion
It is seldom considered to adapt the decision boundary for new representations and in this paper we propose a Supervised Contrastive learning framework with adaptive classification criterion for Continual Learning (SCCL), In our method, a contrastive loss is used to directly learn representations for different tasks and a limited number of data samples are saved as the classification criterion.
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.
An Efficient Framework for Few-shot Skeleton-based Temporal Action Segmentation
This study proposes an efficient framework for the few-shot skeleton-based TAS, including a data augmentation method and an improved model.
Automatic dataset generation for specific object detection
In the past decade, object detection tasks are defined mostly by large public datasets.
A New Evaluation Method: Evaluation Data and Metrics for Chinese Grammar Error Correction
In terms of the reference-based metric, we introduce sentence-level accuracy and char-level BLEU to evaluate the corrected sentences.
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)
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Multilingual Text Classification for Dravidian Languages
On the other hand, in view of the problem that the model cannot well recognize and utilize the correlation among languages, we further proposed a language-specific representation module to enrich semantic information for the model.
