47 citations · 194 across the 36 of their papers we have counts for
10 papers · 1 filter
Battery-Sim-Agent: Leveraging LLM-Agent for Inverse Battery Parameter Estimation
Jiawei Chen, Xiaofan Gui, Shikai Fang +4
Parameterizing high-fidelity "digital twins" of batteries is a critical yet challenging inverse problem that hinders the pace of battery innovation. Prevailing methods formulate th…
Agent^2 RL-Bench: Can LLM Agents Engineer Agentic RL Post-Training?
Wanyi Chen, Xiao Yang, Xu Yang +7
We introduce Agent2 RL-Bench, a compact diagnostic benchmark for evaluating agentic RL post-training, which tests whether LLM agents can autonomously design, implement, debug, and…
FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents
Qizheng Li, Yifei Zhang, Xiao Yang +4
Fine-tuning large language models for vertical domains remains labor-intensive, requiring practitioners to curate data, configure training, and iteratively diagnose model behavior.…
R&D-Agent: An LLM-Agent Framework Towards Autonomous Data Science
Xu Yang, Xiao Yang, Shikai Fang +13
Recent advances in AI and ML have transformed data science, yet increasing complexity and expertise requirements continue to hinder progress. Although crowd-sourcing platforms alle…
Collaborative Evolving Strategy for Automatic Data-Centric Development
Xu Yang, Haotian Chen, Wenjun Feng +7
Artificial Intelligence (AI) significantly influences many fields, largely thanks to the vast amounts of high-quality data for machine learning models. The emphasis is now on a dat…
Towards Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye +6
The progress of humanity is driven by those successful discoveries accompanied by countless failed experiments. Researchers often seek the potential research directions by reading…
Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu +4
In the wake of relentless digital transformation, data-driven solutions are emerging as powerful tools to address multifarious industrial tasks such as forecasting, anomaly detecti…
Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance
Yuchen Fang, Zhenggang Tang, Kan Ren +7
Order execution is a fundamental task in quantitative finance, aiming at finishing acquisition or liquidation for a number of trading orders of the specific assets. Recent advance…
Scalable and Safe Remediation of Defective Actions in Self-Learning Conversational Systems
Sarthak Ahuja, Mohammad Kachuee, Fateme Sheikholeslami +2
Off-Policy reinforcement learning has been a driving force for the state-of-the-art conversational AIs leading to more natural humanagent interactions and improving the user satisf…
KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings
Zhiping Luo, Wentao Xu, Weiqing Liu +3
Learning the embeddings of knowledge graphs (KG) is vital in artificial intelligence, and can benefit various downstream applications, such as recommendation and question answering…