activity
20242026
most citedSurvey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods

146 citations · 150 across the 6 of their papers we have counts for

collaborators

9 papers

cs.AI2026

FDE-Bench: Evaluating End-to-End Delivery from Underspecified Real-World Business Requests

Huaiming Li, Can Huang, Chufan Wu +18

Real-world business requests often leave key requirements unstated because frontline practitioners struggle to articulate rules they know from experience. Forward-deployed engineer…

cs.AI2026

QART: A Quantum-Classical Hybrid Architecture for Long-Horizon Reasoning -- Exploring a Conditional Path toward Quantum Scaling

Lehao Lin, Yuheng Cheng, Guolong Liu +9

Long-horizon reasoning is vulnerable to early errors that compromise later decisions. We present QART, the Quantum-Augmented Reasoning Transformer, a quantum--classical hybrid arch…

cs.CL2026

RePro: Proof-Verified Benchmark Rewriting for Reliable Evaluation of LLM Mathematical Problem Solving

Xiyuan Zhou, Zhuoqi Li, Xinlei Wang +6

Data contamination undermines the reliable evaluation of large language models (LLMs) on mathematical problem solving. While rewriting-based evaluation mitigates memorization, exis…

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.AI2025

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…

cs.CL2025

Multi-Objective Large Language Model Unlearning

Zibin Pan, Shuwen Zhang, Yuesheng Zheng +3

Machine unlearning in the domain of large language models (LLMs) has attracted great attention recently, which aims to effectively eliminate undesirable behaviors from LLMs without…

cs.AI2024★ 3 cited

ElecBench: a Power Dispatch Evaluation Benchmark for Large Language Models

Xiyuan Zhou, Huan Zhao, Yuheng Cheng +6

In response to the urgent demand for grid stability and the complex challenges posed by renewable energy integration and electricity market dynamics, the power sector increasingly…

eess.SY2024★ 1 cited

GAIA -- A Large Language Model for Advanced Power Dispatch

Yuheng Cheng, Huan Zhao, Xiyuan Zhou +3

Power dispatch is essential for providing stable, cost-effective, and eco-friendly electricity to society. However, traditional methods falter as power systems grow in scale and co…

cs.LG2024★ 146 cited

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…