Nirmalendu Prakash

According to our database, Nirmalendu Prakash authored at least 10 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Understanding Refusal in Language Models with Sparse Autoencoders.

Wei Jie Yeo, Nirmalendu Prakash, Clement Neo, Roy Ka-Wei Lee, Erik Cambria, Ranjan Satapathy

CoRR, May, 2025

Activation Space Interventions Can Be Transferred Between Large Language Models.

Narmeen Oozeer, Dhruv Nathawani, Nirmalendu Prakash, Michael Lan, Abir Harrasse, Amirali Abdullah

CoRR, March, 2025

2024

Interpreting Bias in Large Language Models: A Feature-Based Approach.

Nirmalendu Prakash, Roy Ka-Wei Lee

CoRR, 2024

SGHateCheck: Functional Tests for Detecting Hate Speech in Low-Resource Languages of Singapore.

Ri Chi Ng, Nirmalendu Prakash, Ming Shan Hee, Kenny Tsu Wei Choo, Roy Ka-Wei Lee

CoRR, 2024

2023

PromptMTopic: Unsupervised Multimodal Topic Modeling of Memes using Large Language Models.

Nirmalendu Prakash, Han Wang, Nguyen-Khoi Hoang, Ming Shan Hee, Roy Ka-Wei Lee

CoRR, 2023

TotalDefMeme: A Multi-Attribute Meme dataset on Total Defence in Singapore.

Nirmalendu Prakash, Ming Shan Hee, Roy Ka-Wei Lee

Proceedings of the 14th Conference on ACM Multimedia Systems, 2023

PromptMTopic: Unsupervised Multimodal Topic Modeling of Memes using Large Language Models.

Nirmalendu Prakash, Han Wang, Nguyen-Khoi Hoang, Ming Shan Hee, Roy Ka-Wei Lee

Proceedings of the 31st ACM International Conference on Multimedia, 2023

MATK: The Meme Analytical Tool Kit.

Ming Shan Hee, Aditi Kumaresan, Nguyen-Khoi Hoang, Nirmalendu Prakash, Rui Cao, Roy Ka-Wei Lee

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Layered Bias: Interpreting Bias in Pretrained Large Language Models.

Nirmalendu Prakash, Roy Ka-Wei Lee

Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP, 2023

Prompting Large Language Models for Topic Modeling.

Han Wang, Nirmalendu Prakash, Nguyen-Khoi Hoang, Ming Shan Hee, Usman Naseem, Roy Ka-Wei Lee

Proceedings of the IEEE International Conference on Big Data, 2023