1 citations · 3 across the 8 of their papers we have counts for
8 papers
Language Steering for Multilingual In-Context Learning
Neeraja Kirtane, Kuan-Hao Huang
If multilingual language model representations contain separable language-associated structure, then shifting between languages may require only simple activation-space interventio…
MathRobust-LV: Evaluation of Large Language Models' Robustness to Linguistic Variations in Mathematical Reasoning
Neeraja Kirtane, Yuvraj Khanna, Peter Relan
Large language models excel on math benchmarks, but their math reasoning robustness to linguistic variation is underexplored. While recent work increasingly treats high-difficulty…
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…
FactCheckmate: Preemptively Detecting and Mitigating Hallucinations in LMs
Deema Alnuhait, Neeraja Kirtane, Muhammad Khalifa +1
Language models (LMs) hallucinate. We inquire: Can we detect and mitigate hallucinations before they happen? This work answers this research question in the positive, by showing th…
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…