3 papers
cs.LG2026
CoPeP: Benchmarking Continual Pretraining for Protein Language Models
Darshan Patil, Pranshu Malviya, Mathieu Reymond +2
Protein language models (pLMs) have recently gained significant attention for their ability to uncover relationships between sequence, structure, and function from evolutionary sta…
cs.LG2025
Manifold Metric: A Loss Landscape Approach for Predicting Model Performance
Pranshu Malviya, Jerry Huang, Aristide Baratin +2
Determining the optimal model for a given task often requires training multiple models from scratch, which becomes impractical as dataset and model sizes grow. A more efficient alt…
cs.LG2024
Torque-Aware Momentum
Pranshu Malviya, Goncalo Mordido, Aristide Baratin +4
Efficiently exploring complex loss landscapes is key to the performance of deep neural networks. While momentum-based optimizers are widely used in state-of-the-art setups, classic…