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Neha Hulkund

2 accepted papers

2026

A Critical Look at Targeted Instruction Selection: Disentangling What Matters (and What Doesn’t)

ICML 2026poster

Instruction fine-tuning of large language models (LLMs) often involves selecting a subset of instruction training data from a large candidate pool, using a small query set from the target task. Despite growing interest, the literature on targeted instruction selection remains fragmented and opaque: …

Cited by 0SourceScholar
2024

Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent

ICML 2024poster

We present a novel approach for differentially private data synthesis of protected tabular datasets, a relevant task in highly sensitive domains such as healthcare and government. Current state-of-the-art methods predominantly use marginal-based approaches, where a dataset is generated from private…