2 papers
cs.LG2026
ContextEvolve: Multi-Agent Context Compression for Systems Code Optimization
Hongyuan Su, Yu Zheng, Yong Li
Large language models are transforming systems research by automating the discovery of performance-critical algorithms for computer systems. Despite plausible codes generated by LL…
cs.AI2025
The Thinking Spectrum: An Empirical Study of Tunable Reasoning in LLMs through Model Merging
Xiaochong Lan, Yu Zheng, Shiteng Cao +1
The growing demand for large language models (LLMs) with tunable reasoning capabilities in many real-world applications highlights a critical need for methods that can efficiently…