← Search

Prateek Chanda

5 accepted papers

2026

Minibatch selection for Language Models via Partition Matroid Constrained Gradient Matching

ICML 2026poster

Training Large Language Models (LLMs) on heterogeneous datasets requires optimizing domain representations to balance convergence speed and domain coverage. While recent methods reduce computational overhead by selecting high-quality data subsets, they typically perform selection independently per d…

Cited by 0SourceScholar
2026

Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning

ICLR 2026poster

Continual learning in large language models (LLMs) is prone to catastrophic forgetting, where adapting to new tasks significantly degrades performance on previously learned ones. Existing parameter-efficient methods often limit model expressivity or introduce new parameters per task, creating scalab…

Cited by 0SourcecodeScholar
2025

Bandit Guided Submodular Curriculum for Adaptive Subset Selection

NeurIPS 2025poster

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 difficulty scores in curriculum learning. We reinterpret adaptive subset selection and formulate it as a multi-armed ba…

Cited by 0SourcecodeScholar
2024

Few shot chain-of-thought driven reasoning to prompt LLMs for open-ended medical question answering

EMNLP 2024finding

In this paper, we propose a modified version of the MedQA-USMLE dataset, named MEDQA-OPEN, which contains open-ended medical questions without options to mimic clinical scenarios, along with clinician-approved reasoned answers. Additionally, we implement a prompt driven by Chain of Thought (CoT) rea…