Qi Liu

Estimation of leaf nitrogen concentration at different leaf positions in rice based on UAV RGB images combined with machine-learning algorithms

Boteng Sun, Wei Zhou, Songde Huang, Qi Liu, Shilin Zhu, Jinyue Guo, et al.

Clarify Before Executing: A Self-Evolving Agent for Resolving Intent Asymmetry in 3D Tool Orchestration

Xiaoye Zhu, Weixin Li, Junan Huo, Bozhong Wang, Jia Zeng, Yi Yang, et al.

A fundamental intent asymmetry plagues modern 3D asset creation: while state-of-the-art 3D toolchains demand precise, executable parameters, ordinary users typically provide vague, underspecified instructions. Current 3D agents treat this ambiguity as noise, defaulting to blind e…Read more

MathCoPilot: An Interactive System for Human-AI Symbiotic Paradigm of Mathematical Research

Junjie Zhang, Jiayu Liu, Wenbin Liu, Zhenya Huang, Doudou Wang, Yan Jiang, et al.

Existing LLM-based theorem provers have achieved impressive results on formal mathematics benchmarks, yet they remain confined to acting as autonomous agents that prove a stated proposition. In this paper, we propose MathCoPilot, a human-in-the-loop system that embodies a new hum…Read more

Learning Robust Execution in Robotic Manipulation with Agentic Reinforcement Learning

Xiaopeng Zhang, Yueyang Weng, Qi Liu, Yongjin Mu, Yanjie Li

Robotic manipulation poses fundamental challenges due to uncertainty, long-horizon execution, and compounding errors, which can easily destabilize execution and lead to task failure. Although recent vision-language-action (VLA) models exhibit strong generalization, they typically…Read more

UR-VC: Unsupervised Robotic Value Correction for Time-Derived Progress Proxies

Lirui Zhao, Modi Shi, Li Chen, Qi Liu, Ping Luo, Hongyang Li

Modern robot learning systems increasingly rely on dense progress or value signals to evaluate intermediate states, guide policy learning, and detect task completion, making the quality of these signals critical. Since such dense labels are rarely available at scale, normalized t…Read more

PrismAD: Decoupled Planning via Semantic Mixture-of-Planners for End-to-End Autonomous Driving

Kang Ding, Zhigui Lin, Hongsong Wang, Jie Gui, Qi Liu, Zhe Wang, et al.

This letter presents PrismAD, a decoupled end-to-end autonomous driving framework based on a Semantic Mixture-of-Planners. Existing planners usually aggregate heterogeneous scene tokens into a coupled representation space, forcing a single planning branch to jointly model agent i…Read more

Dual-Satellite Doppler Accuracy Prediction and Geometry Selection for Sparse LEO Signals of Opportunity

Qi Liu, Marc Fernández-Temprado, Antoni Reus-Bergas, Shuguo Pan, Wang Gao, Gonzalo Seco-Granados, et al.

Low Earth Orbit (LEO) satellites have emerged as a promising complement to GNSS for positioning in signal challenged environments. In sparse LEO signals of opportunity scenarios, Doppler positioning often relies on only one or two satellite passes, making positioning accuracy hig…Read more

CGGS: Consistency-Augmented Geometric Gaussian Splatting for Ego-Centric 3D Scene Generation

Zhenyu Sun, Xiaohan Zhang, Qi Liu, Huan Wang

Challenges remain in ego-centric 3D scene generation due to limited view overlap and the dominant influence of individual perspectives on scene interpretation. These factors hinder the creation of viewpoint-consistent and semantically aligned visual content, as well as the constr…Read more

Harness-Aware Self-Evolving: Co-Evolving Model Weights, Harness, and Task Solutions

Haochen Luo, Yi Huang, Sichun Luo, Fengyuan Liu, Lei Li, Zefa Hu, et al.

Self-evolving frameworks usually optimize task solutions while treating the surrounding harness as fixed. We introduce Harness-Aware Self-Evolving (HASE), an agentic reinforcement-learning framework in which a single model can generate task solutions or edit selected harness comp…Read more

AnchorVLA: Bridging Discrete Decisions and Continuous Trajectories for Vision-Language-Action Planning

Qi Liu, Yabei Li, Hongsong Wang, Heng Zhang, Lei He

Autonomous driving planning requires translating navigation intent, traffic rules, dynamic interactions, and language instructions into executable continuous trajectories. Vision-Language-Action models have been introduced into driving planning to improve long-tail generalization…Read more

Towards transferable lightweight neuromorphic computing through a model-free temporal-switch framework

Zefeng Zhang, Chao Li, Siyao Chen, Pei Chen, Bo-Wei Qin, Xumeng Zhang, et al.

Lightweight neuromorphic computing offers a promising route to efficient AI, with particular benefits for resource-constrained edge deployments. However, its scalable deployment that can reliably transfer the expected performance has long been hindered by device-to-device variati…Read more

Digital Empowerment, Novel Productive Forces, and Regional Green Innovation Efficiency: Causal Inference Based on Spatial Difference-in-Differences and Double Machine Learning Approaches

Qi Liu, Siyu Liu, Tianning Guan, Luhan Yu, Zemenghong Bao, Yuzhu Wen, et al.

Amidst the dual challenges of escalating ecological environmental pressures and economic transformation globally, green innovation emerges as a pivotal pathway toward achieving high-quality sustainable development. To elucidate how digitalization and novel productive forces syner…Read more

Navigating Data Corruption in Machine Learning: Balancing Quality, Quantity, and Imputation Strategies

Qi Liu, Wanjing Ma

Data corruption, including missing and noisy entries, is a common challenge in real-world machine learning. This paper examines its impact and mitigation strategies through two experimental setups: supervised NLP tasks (NLP-SL) and deep reinforcement learning for traffic signal c…Read more

Digital Government Construction, Bidirectional Interaction Between Technological and Spiritual Civilization, and Achieving Dual Control of Sustainable Energy: Causal Inference Using Spatial DID and Dual Machine Learning

Xinle Zheng, Linrong Yu, Qi Liu, Rui Xu, Junyan Tang, Xinyuan Yu, et al.

This study aims to elucidate the mechanisms through which digital government construction influences regional dual control of energy consumption (encompassing both the total volume and intensity of energy use), with a particular emphasis on exploring its indirect effects mediated…Read more

ANP-I: A 28-nm 1.5-pJ/SOP Asynchronous Spiking Neural Network Processor Enabling Sub-0.1-<i>μ</i> J/Sample On-Chip Learning for Edge-AI Applications

Jilin Zhang, Dexuan Huo, Jian Zhang, Chunqi Qian, Qi Liu, Liyang Pan, et al.