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Hongyi Jin

2 accepted papers

2026

Which Reasoning Traces Are Worth Generating Further? Data Curation for Training Reasoning Models

ICML 2026poster

Supervised fine-tuning (SFT) on a small high-quality set of long reasoning traces is an effective way to enable strong reasoning abilities for Large Language Models (LLMs). However, curating a high-quality SFT data requires generating a large pool of long Chain of Thoughts (CoTs), and filtering the …

Cited by 0Source ↗Scholar ↗
2022

Tensor Program Optimization with Probabilistic Programs

NeurIPS 2022accept

Automatic optimization for tensor programs becomes increasingly important as we deploy deep learning in various environments, and efficient optimization relies on a rich search space and effective search. Most existing efforts adopt a search space which lacks the ability to efficiently enable domain…

Cited by 36Source ↗PDF ↗Scholar ↗