Identification of Emergency Blood Donation Request on Twitter

1 code implementation • WS 2018 • Puneet Mathur, Meghna Ayyar, Sahil Chopra, Simra Shahid, Laiba Mehnaz, Rajiv Shah

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.

Suggestion Mining from Online Reviews using ULMFiT

1 code implementation • 19 Apr 2019 • Sarthak Anand, Debanjan Mahata, Kartik Aggarwal, Laiba Mehnaz, Simra Shahid, Haimin Zhang, Yaman Kumar, Rajiv Ratn Shah, Karan Uppal

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.

General Classification Language Modelling +4

Identifying Offensive Posts and Targeted Offense from Twitter

no code implementations • 19 Apr 2019 • Haimin Zhang, Debanjan Mahata, Simra Shahid, Laiba Mehnaz, Sarthak Anand, Yaman Singla, Rajiv Ratn Shah, Karan Uppal

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.

GupShup: An Annotated Corpus for Abstractive Summarization of Open-Domain Code-Switched Conversations

no code implementations • 17 Apr 2021 • Laiba Mehnaz, Debanjan Mahata, Rakesh Gosangi, Uma Sushmitha Gunturi, Riya Jain, Gauri Gupta, Amardeep Kumar, Isabelle Lee, Anish Acharya, Rajiv Ratn Shah

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.

Abstractive Text Summarization

MLCommons Cloud Masking Benchmark with Early Stopping

no code implementations • 11 Dec 2023 • Varshitha Chennamsetti, Gregor von Laszewski, Ruochen Gu, Laiba Mehnaz, Juri Papay, Samuel Jackson, Jeyan Thiyagalingam, Sergey V. Samsonau, Geoffrey C. Fox

We provide a description of the cloud masking benchmark, as well as a summary of our submission to MLCommons on the benchmark experiment we conducted.

Improvements & Evaluations on the MLCommons CloudMask Benchmark

no code implementations • 7 Mar 2024 • Varshitha Chennamsetti, Laiba Mehnaz, Dan Zhao, Banani Ghosh, Sergey V. Samsonau

In this paper, we report the performance benchmarking results of deep learning models on MLCommons' Science cloud-masking benchmark using a high-performance computing cluster at New York University (NYU): NYU Greene.

Benchmarking

Analyzing the Domain Robustness of Pretrained Language Models, Layer by Layer

no code implementations • EACL (AdaptNLP) 2021 • Abhinav Ramesh Kashyap, Laiba Mehnaz, Bhavitvya Malik, Abdul Waheed, Devamanyu Hazarika, Min-Yen Kan, Rajiv Ratn Shah

The robustness of pretrained language models(PLMs) is generally measured using performance drops on two or more domains.

Automatic Classification of Tweets Mentioning a Medication Using Pre-trained Sentence Encoders

no code implementations • SMM4H (COLING) 2020 • Laiba Mehnaz

This paper describes our submission to the 5th edition of the Social Media Mining for Health Applications (SMM4H) shared task 1.

Sentence text-classification +1

GupShup: Summarizing Open-Domain Code-Switched Conversations

1 code implementation • EMNLP 2021 • Laiba Mehnaz, Debanjan Mahata, Rakesh Gosangi, Uma Sushmitha Gunturi, Riya Jain, Gauri Gupta, Amardeep Kumar, Isabelle G. Lee, Anish Acharya, Rajiv Ratn Shah

Code-switching is the communication phenomenon where the speakers switch between different languages during a conversation.

Abstractive Text Summarization