3 papers
cs.LG2026
Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning
Prateek Chanda, Saral Sureka, Parth Pratim Chatterjee +3
Supervised fine-tuning performance for large language models depends strongly on how training budget is distributed across a heterogeneous set of tasks. In practice, mixtures are o…
cs.LG2025
Bandit Guided Submodular Curriculum for Adaptive Subset Selection
Prateek Chanda, Prayas Agrawal, Saral Sureka +3
Traditional curriculum learning proceeds from easy to hard samples, yet defining a reliable notion of difficulty remains elusive. Prior work has used submodular functions to induce…
cs.CL2025
PARAM-1 BharatGen 2.9B Model
Kundeshwar Pundalik, Piyush Sawarkar, Nihar Sahoo +19
Large Language Models (LLMs) have emerged as powerful general-purpose reasoning systems, yet their development remains dominated by English-centric data, architectures, and optimiz…