6 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CL2025
ParaThinker: Native Parallel Thinking as a New Paradigm to Scale LLM Test-time Compute
Hao Wen, Yifan Su, Feifei Zhang +4
Recent advances in Large Language Models (LLMs) have been driven by test-time compute scaling - a strategy that improves reasoning by generating longer, sequential thought processe…
cs.AI2025
An Empirical Study of LLM Reasoning Ability Under Strict Output Length Constraint
Yi Sun, Han Wang, Jiaqiang Li +8
Recent work has demonstrated the remarkable potential of Large Language Models (LLMs) in test-time scaling. By making models think before answering, they are able to achieve much h…
cs.AI2025★ 6 cited
Data Center Cooling System Optimization Using Offline Reinforcement Learning
Xianyuan Zhan, Xiangyu Zhu, Peng Cheng +10
The recent advances in information technology and artificial intelligence have fueled a rapid expansion of the data center (DC) industry worldwide, accompanied by an immense appeti…