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Found 11 papers, 1 papers with code
Findings of the Shared Task on Machine Translation in Dravidian languages
This paper describes the datasets used, the methodology used for the evaluation of participants, and the experiments’ overall results.
Findings of the Shared Task on Offensive Language Identification in Tamil, Malayalam, and Kannada
Detecting offensive language in social media in local languages is critical for moderating user-generated content.
NITK-UoH: Tamil-Telugu Machine Translation Systems for the WMT21 Similar Language Translation Task
The OpenNMT-py toolkit has been used to create quick prototypes of the systems, following which models have been trained on the training datasets containing the parallel corpus and finally the models have been evaluated on the dev datasets provided as part of the task.
NITK NLP at FinCausal-2020 Task 1 Using BERT and Linear models.
FinCausal-2020 is the shared task which focuses on the causality detection of factual data for financial analysis.
Towards Unsupervised Question Answering System with Multi-level Summarization for Legal Text
This paper summarizes Team SCaLAR's work on SemEval-2024 Task 5: Legal Argument Reasoning in Civil Procedure.
Representation Learning in Continuous-Time Dynamic Signed Networks
Modeling such dynamics of signed networks is crucial to understanding the evolution of polarization in the network and enabling effective prediction of the signed structure (i. e., link signs and signed weights) in the future.
Leveraging Multimodal Behavioral Analytics for Automated Job Interview Performance Assessment and Feedback
Such analysis is then used to provide constructive feedback to the interviewee for their behavioral cues and body language.
Deep-Net: Deep Neural Network for Cyber Security Use Cases
In this paper, we attempt to apply DNNs on three different cyber security use cases: Android malware classification, incident detection and fraud detection.
Deep Health Care Text Classification
This working note presents the Recurrent neural network (RNN) and Long short-term memory (LSTM) based embedding for automatic health text classification in the social media mining.
Vector Space Model as Cognitive Space for Text Classification
The objective of the task is to find the sociolect aspects of the users from their tweets.
