3 papers
cs.LG2026
A Critical Look at Targeted Instruction Selection: Disentangling What Matters (and What Doesn't)
Nihal V. Nayak, Paula Rodriguez-Diaz, Neha Hulkund +2
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…
cs.SE2026
GenAI for Systems: Recurring Challenges and Design Principles from Software to Silicon
Arya Tschand, Chenyu Wang, Zishen Wan +21
Generative AI is reshaping how computing systems are designed, optimized, and built, yet research remains fragmented across software, architecture, and chip design communities. Thi…
cs.LG2025
What is the Right Notion of Distance between Predict-then-Optimize Tasks?
Paula Rodriguez-Diaz, Lingkai Kong, Kai Wang +2
Comparing datasets is a fundamental task in machine learning, essential for various learning paradigms-from evaluating train and test datasets for model generalization to using dat…