collaborators

5 papers

cs.CY2026

Hugging Carbon: Quantifying the Training Carbon Emissions of AI Models at Scale

Xinlei Wang, Ruibo Ming, Jing Qiu +2

The scaling-law era has transformed artificial intelligence (AI) from research into a global industry, but its rapid growth also raises concerns over energy usage, carbon emissions…

cs.AI2026

EngiAgent: Fully Connected Coordination of LLM Agents for Solving Open-ended Engineering Problems with Feasible Solutions

Xiyuan Zhou, Ruixi Zou, Xinlei Wang +4

Engineering problem solving is central to real-world decision-making, requiring mathematical formulations that not only represent complex problems but also produce feasible solutio…

cs.AI2026

EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving

Xiyuan Zhou, Xinlei Wang, Yirui He +9

Large language models (LLMs) have shown strong performance on mathematical reasoning under well-defined conditions. However, real-world engineering problems involve uncertainty, co…

eess.SY2024

Coordinated Power Smoothing Control for Wind Storage Integrated System with Physics-informed Deep Reinforcement Learning

Shuyi Wang, Huan Zhao, Yuji Cao +4

The Wind Storage Integrated System with Power Smoothing Control (PSC) has emerged as a promising solution to ensure both efficient and reliable wind energy generation. However, exi…

cs.LG2024

Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods

Yuji Cao, Huan Zhao, Yuheng Cheng +7

With extensive pre-trained knowledge and high-level general capabilities, large language models (LLMs) emerge as a promising avenue to augment reinforcement learning (RL) in aspect…