1 citations · 3 across the 5 of their papers we have counts for
5 papers
LLMs are Vulnerable to Malicious Prompts Disguised as Scientific Language
Yubin Ge, Neeraja Kirtane, Hao Peng +1
As large language models (LLMs) have been deployed in various real-world settings, concerns about the harm they may propagate have grown. Various jailbreaking techniques have been…
ReGrAt: Regularization in Graphs using Attention to handle class imbalance
Neeraja Kirtane, Jeshuren Chelladurai, Balaraman Ravindran +1
Node classification is an important task to solve in graph-based learning. Even though a lot of work has been done in this field, imbalance is neglected. Real-world data is not per…
Efficient Gender Debiasing of Pre-trained Indic Language Models
Neeraja Kirtane, V Manushree, Aditya Kane
The gender bias present in the data on which language models are pre-trained gets reflected in the systems that use these models. The model's intrinsic gender bias shows an outdate…
Mitigating Gender Stereotypes in Hindi and Marathi
Neeraja Kirtane, Tanvi Anand
As the use of natural language processing increases in our day-to-day life, the need to address gender bias inherent in these systems also amplifies. This is because the inherent b…
Transformer based ensemble for emotion detection
Aditya Kane, Shantanu Patankar, Sahil Khose +1
Detecting emotions in languages is important to accomplish a complete interaction between humans and machines. This paper describes our contribution to the WASSA 2022 shared task w…