Author

Parameswaran Kamalaruban

3 papers indexed here

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#artificial intelligence Preprint Oct 2026

Latent space bias directions in LLMs capture confidence, not fairness

Activation steering has gained popularity as a lightweight inference-time debiasing technique for large language models. However, prior work reports that steering vectors generalise poorly, with unintended effects on model performance and limited transfer to new datasets. Our work analyses what the debiasing direction...

Stephanie Buttigieg, Maeve Madigan, P. Kamalaruban et al. · 1 citation · ⚡1

Preprint Aug 2026

Fairness-Aware Test-Time Prompt Tuning

FairTPT is developed, a novel fairness-aware episodic TTA method that jointly minimizes target marginal entropy while maximizing spurious marginal entropy through soft-prompt tuning and establishes a foundation for robust TTA, which is essential for achieving fairness in practice.

Yoann L. Launay, P. Kamalaruban, Tom Kempton et al. · 0 citations

Preprint Aug 2026

MINT: A Universal Zero-Shot Predictor for Transaction Data

The Multimodal Instruction Network for Transactions (MINT), a framework that connects a pretrained transaction sequence encoder to a decoder-only LLM through lightweight embedding injection, transaction-language alignment, and instruction tuning, achieves state-of-the-art predictive question-answering performance in bo...

Parameswaran Kamalaruban, Viktor Drobnyi, Maeve Madigan et al. · 0 citations