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Found 7 papers, 3 papers with code
GupShup: Summarizing Open-Domain Code-Switched Conversations
Code-switching is the communication phenomenon where the speakers switch between different languages during a conversation.
Automatic Classification of Tweets Mentioning a Medication Using Pre-trained Sentence Encoders
This paper describes our submission to the 5th edition of the Social Media Mining for Health Applications (SMM4H) shared task 1.
Analyzing the Domain Robustness of Pretrained Language Models, Layer by Layer
The robustness of pretrained language models(PLMs) is generally measured using performance drops on two or more domains.
GupShup: An Annotated Corpus for Abstractive Summarization of Open-Domain Code-Switched Conversations
Towards this objective, we introduce abstractive summarization of Hindi-English code-switched conversations and develop the first code-switched conversation summarization dataset - GupShup, which contains over 6, 831 conversations in Hindi-English and their corresponding human-annotated summaries in English and Hindi-English.
Identifying Offensive Posts and Targeted Offense from Twitter
In this paper we present our approach and the system description for Sub-task A and Sub Task B of SemEval 2019 Task 6: Identifying and Categorizing Offensive Language in Social Media.
Suggestion Mining from Online Reviews using ULMFiT
In this paper we present our approach and the system description for Sub Task A of SemEval 2019 Task 9: Suggestion Mining from Online Reviews and Forums.
Identification of Emergency Blood Donation Request on Twitter
Social media-based text mining in healthcare has received special attention in recent times due to the enhanced accessibility of social media sites like Twitter.
