Author

Utkarsh Agarwal

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Preprint Aug 2026

Multi-Objective Bayesian Optimization for Model Merging

Results show that multi-objective Bayesian optimization is valuable as a search layer for expressive merge parameterizations in model merging and introduce MOBO-Merge, a merge-operator agnostic framework that uses multi-objective Bayesian optimization to approximate the Pareto front under a limited evaluation budget.

Utkarsh Agarwal, V. Bonagiri, Raul Astudillo et al. · 0 citations

Preprint Aug 2026

SurakshaEval: An Indic Safety Benchmark for Multilingual LLMs

SurakshaEval is introduced, a novel safety benchmark composed of human-written prompts spanning real-world scenarios, explicitly designed for ten major Indian languages - Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Punjabi, Tamil, and Telugu - along with English.

Debopriyo Banerjee, K. R. Kavitha, Angana Borah et al. · 0 citations