2 citations · 2 across the 1 of their papers we have counts for
8 papers · 1 filter
Generation and De-Identification of Indian Clinical Discharge Summaries using LLMs
Sanjeet Singh, Shreya Gupta, Niralee Gupta +4
The consequences of a healthcare data breach can be devastating for the patients, providers, and payers. The average financial impact of a data breach in recent months has been est…
iSign: A Benchmark for Indian Sign Language Processing
Abhinav Joshi, Romit Mohanty, Mounika Kanakanti +4
Indian Sign Language has limited resources for developing machine learning and data-driven approaches for automated language processing. Though text/audio-based language processing…
IITK at SemEval-2024 Task 10: Who is the speaker? Improving Emotion Recognition and Flip Reasoning in Conversations via Speaker Embeddings
Shubham Patel, Divyaksh Shukla, Ashutosh Modi
This paper presents our approach for the SemEval-2024 Task 10: Emotion Discovery and Reasoning its Flip in Conversations. For the Emotion Recognition in Conversations (ERC) task, w…
IITK at SemEval-2024 Task 4: Hierarchical Embeddings for Detection of Persuasion Techniques in Memes
Shreenaga Chikoti, Shrey Mehta, Ashutosh Modi
Memes are one of the most popular types of content used in an online disinformation campaign. They are primarily effective on social media platforms since they can easily reach man…
IITK at SemEval-2024 Task 1: Contrastive Learning and Autoencoders for Semantic Textual Relatedness in Multilingual Texts
Udvas Basak, Rajarshi Dutta, Shivam Pandey +1
This paper describes our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness. The challenge is focused on automatically detecting the degree of relatedness b…
IITK at SemEval-2024 Task 2: Exploring the Capabilities of LLMs for Safe Biomedical Natural Language Inference for Clinical Trials
Shreyasi Mandal, Ashutosh Modi
Large Language models (LLMs) have demonstrated state-of-the-art performance in various natural language processing (NLP) tasks across multiple domains, yet they are prone to shortc…