3 papers
cs.LG2026
Distilled Reinforcement Learning for LLM Post-training
Chen Wang, Zhaochun Li, Jionghao Bai +4
Large language model (LLM) post-training is essential for improving reasoning, adaptation, and alignment. Existing methods mainly follow two paradigms: reinforcement learning (RL)…
cs.PL2026
TENSURE: Fuzzing Sparse Tensor Compilers (Registered Report)
Kabilan Mahathevan, Yining Zhang, Muhammad Ali Gulzar +1
Sparse Tensor Compilers (STCs) have emerged as critical infrastructure for optimizing high-dimensional data analytics and machine learning workloads. The STCs must synthesize compl…
cs.CY2025
OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists
Chenyang Shao, Dehao Huang, Yu Li +18
With the rapid development of Large Language Models (LLMs), AI agents have demonstrated increasing proficiency in scientific tasks, ranging from hypothesis generation and experimen…