卢杰

2026

Large Language Models Meet Energy Systems: Opportunities, Challenges, and Future Perspectives

Applied Energy

DOI

2026

Confidence-driven HVAC component recognition integrating LLMs and computer vision

Building Simulation

DOI

2026

An Electrical Motor Bearing Fault Diagnosis Method based on Physics-prior Constrained Semi-supervised Domain Generalization

2026 IEEE 3rd International Conference on Electrical Power Systems and Intelligent Control (EPSIC)

DOI

2026

Large Language Model-Based Method for HVAC System Control Code Automatic Generation

Buildings

DOI

2026

LightLLM4FDD: Domain-specific lightweight large language models for fault detection and diagnosis in building HVAC systems

Advanced Engineering Informatics

DOI

2025

Hybrid data-driven and physics-based fast building cooling demand modeling method for large-scale building demand response control

Journal of Building Engineering

DOI

2025

Automated data-driven building energy load prediction method based on generative pre-trained transformers (GPT)

Energy

DOI

2025

Automated building energy modeling for energy retrofits using a large language model-based multi-agent framework

iScience

DOI

2024

Evaluation of large language models (LLMs) on the mastery of knowledge and skills in the heating, ventilation and air conditioning (HVAC) industry

Energy and Built Environment

DOI

2024

End-to-end data-driven modeling framework for automated and trustworthy short-term building energy load forecasting

Building Simulation

DOI

2024

Automated data mining framework for building energy conservation aided by generative pre-trained transformers (GPT)

Energy and Buildings

DOI

2024

Self-attention variational autoencoder-based method for incomplete model parameter imputation of digital twin building energy systems

Energy and Buildings

DOI

2024

A prior-knowledge-based time series model for heat demand prediction of district heating systems

Applied Thermal Engineering

DOI

2024

Graph convolutional networks-based method for uncertainty quantification of building design loads

Building Simulation

DOI

2023

Stepping beyond your comfort zone: Diffusion-based network analytics for knowledge trajectory recommendation

Journal Of The Association For Information Science And Technology，Vol. 740, No. 70

DOI

2023

Automated machine learning-based building energy load prediction method

Journal of Building Engineering

DOI

2023

Coordinate descent-based model calibration methodology for HVAC subsystems

Building Simulation Conference Proceedings

DOI

2023

Physical informed graph convolutional networks for fast simulation of thermal bridges in building structures

Building Simulation Conference Proceedings

DOI

2013

Ontology-supported case-based reasoning approach for intelligent m-Government emergency response services

Decision Support Systems，Vol. 55, No. 1

DOI

2012

A trust-semantic fusion-based recommendation approach for e-business applications

Decision Support Systems，Vol. 54, No. 1

DOI

Domain-specific large language models for fault diagnosis of heating, ventilation, and air conditioning systems by labeled-data-supervised fine-tuning

Applied Energy

DOI

2026

Generalizable 6D Pose Estimation of Textureless Objects with Planar-based Gaussian Splatting

arXiv preprint

2026

Deep Reinforcement Learning for 6G AI-RAN: A Comprehensive Survey

arXiv preprint

2026

Demystifying Deep Reinforcement Learning: A Neuro-Symbolic Framework for Interpretable Open RAN Automation

arXiv preprint

2026

Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models

arXiv preprint

2026

EExApp: GNN-Based Reinforcement Learning for Radio Unit Energy Optimization in 5G O-RAN

arXiv preprint

2026

Autonomous Drift Learning in Data Streams: A Unified Perspective

arXiv preprint

2026

Towards Robust Endogenous Reasoning: Unifying Drift Adaptation in Non-Stationary Tuning

arXiv preprint

2026

Robust Distributed Nonconvex Optimization Enabling Communication Acceleration and Privacy Protection

arXiv preprint

2026

Delving into Spectral Clustering with Vision-Language Representations

arXiv preprint

2026

A Unifying Primal-Dual Proximal Framework for Distributed Nonconvex Optimization

arXiv preprint

2026

VGAS: Value-Guided Action-Chunk Selection for Few-Shot Vision-Language-Action Adaptation

arXiv preprint

2026

When Recommendation Denoising Meets Popularity Bias: Understanding and Mitigating Their Interaction

arXiv preprint

2026

Unleashing More Actions via Action Compositional Training for VLA Models

arXiv preprint

2026

AC-VLA: Robust Out-of-Distribution Action Execution via Compositional Learning

arXiv preprint

2026

The Sirens' Song: When Proximal Background Context Overshadows Distant Evidence

arXiv preprint

2026

Choosing How to Remember: Adaptive Memory Structures for LLM Agents

arXiv preprint

2026

Agent-Enhanced Heterogeneous Graph RAG for Academic Question Answering

arXiv preprint

DOI

2026

Integrating Health Sensing into Cellular Networks: Human Sleep Monitoring Using 5G Signals

arXiv preprint

2026

Evidence-Aligned Entity Verification for Hallucination Detection in Retrieval-Augmented Generation

arXiv preprint

DOI

2026

UniLab: A Heterogeneous Architecture for Robot RL Beyond GPU-Dominant Paradigms

arXiv preprint

2026

Heterogeneous Information-Bottleneck Coordination Graphs for Multi-Agent Reinforcement Learning

arXiv preprint

2026

GAUGE: Granularity-Adaptive Counterfactual Gating of Evidence for Incomplete Multimodal Classification

arXiv preprint

2026

P-POSEMEM: Projective Semantic Memory for Consistent Language Grounding under Pose-Graph Rewrites

arXiv preprint

2026

TARMM: Scaling Delay-Critical Edge AI Offloading in 5G O-RAN via Temporal Graph Mobility Management

arXiv preprint

2026

Respecting Modality Gap in Post-hoc Out-of-distribution Detection with Pre-trained Vision-Language Models

arXiv preprint

2026

FreKoo++: Learning Continuous Spectral Dynamics for Temporal Domain Generalization

arXiv preprint

2025

Distributed Nonconvex Optimization with Double Privacy Protection and Exact Convergence

arXiv preprint

2025

Autonomous Concept Drift Threshold Determination

arXiv preprint

2025

Bayesian Ego-graph Inference for Networked Multi-Agent Reinforcement Learning

arXiv preprint

2025

Privacy-Utility Trade-off in Data Publication: A Bilevel Optimization Framework with Curvature-Guided Perturbation

arXiv preprint

2025

Bandwidth-constrained Variational Message Encoding for Cooperative Multi-agent Reinforcement Learning

arXiv preprint

2025

On the Provable Importance of Gradients for Language-Assisted Image Clustering

arXiv preprint

2025

Turning Drift into Constraint: Robust Reasoning Alignment in Non-Stationary Multi-Stream Environments

arXiv preprint

2025

Learning Robust Spectral Dynamics for Temporal Domain Generalization

arXiv preprint

2025

Walking the Tightrope: Disentangling Beneficial and Detrimental Drifts in Non-Stationary Custom-Tuning

arXiv preprint

2025

HetGCoT: Heterogeneous Graph-Enhanced Chain-of-Thought LLM Reasoning for Academic Question Answering

arXiv preprint

DOI

2025

Drift-aware Collaborative Assistance Mixture of Experts for Heterogeneous Multistream Learning

arXiv preprint

2025

MiraGe: Multimodal Discriminative Representation Learning for Generalizable AI-Generated Image Detection

arXiv preprint

2025

A Unified Dual Consensus Approach to Distributed Optimization with Globally-Coupled Constraints

arXiv preprint

2025

Autonomous Source Knowledge Selection in Multi-Domain Adaptation

arXiv preprint

2025

From Newborn to Impact: Bias-Aware Citation Prediction

arXiv preprint

2025

Generalized Incremental Learning under Concept Drift across Evolving Data Streams

arXiv preprint

2025

Resilient Contrastive Pre-training under Non-Stationary Drift

arXiv preprint

2025

Near-Real-Time Resource Slicing for QoS Optimization in 5G O-RAN using Deep Reinforcement Learning

arXiv preprint

DOI

2025

TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG

arXiv preprint

2024

A Neighbor-Searching Discrepancy-based Drift Detection Scheme for Learning Evolving Data

arXiv preprint

2024

Adapting Multi-modal Large Language Model to Concept Drift From Pre-training Onwards

arXiv preprint

2024

On the Learnability of Out-of-distribution Detection

arXiv preprint

2024

Layer-diverse Negative Sampling for Graph Neural Networks

arXiv preprint

2024

A Behavior-Aware Approach for Deep Reinforcement Learning in Non-stationary Environments without Known Change Points

arXiv preprint

2024

Group-Aware Coordination Graph for Multi-Agent Reinforcement Learning

arXiv preprint

2024

Globally-Constrained Decentralized Optimization with Variable Coupling

arXiv preprint

2024

Early Concept Drift Detection via Prediction Uncertainty

arXiv preprint

2024

Functional Stochastic Gradient MCMC for Bayesian Neural Networks

arXiv preprint

2024

Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs

arXiv preprint

2024

Sharpness-Aware Cross-Domain Recommendation to Cold-Start Users

arXiv preprint

2024

A Zeroth-Order Proximal Algorithm for Consensus Optimization

arXiv preprint

2023

Distributed Online Optimization with Coupled Inequality Constraints over Unbalanced Directed Networks

arXiv preprint

2023

A Distributed Buffering Drift-Plus-Penalty Algorithm for Coupling Constrained Optimization

arXiv preprint

2023

A Deep Reinforcement Learning Approach to Efficient Distributed Optimization

arXiv preprint

2023

A Mixing-Accelerated Primal-Dual Proximal Algorithm for Distributed Nonconvex Optimization

arXiv preprint

2022

Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples

arXiv preprint

DOI

2022

Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point Processes

arXiv preprint

2022

Multi-class Classification with Fuzzy-feature Observations: Theory and Algorithms

arXiv preprint

DOI

2022

A Stochastic Second-Order Proximal Method for Distributed Optimization

arXiv preprint

2022

Is Out-of-Distribution Detection Learnable?

arXiv preprint

2021

Distributed Optimization with Coupling Constraints

arXiv preprint

2021

Decentralized Statistical Inference with Unrolled Graph Neural Networks

arXiv preprint

2020

A Unifying Approximate Method of Multipliers for Distributed Composite Optimization

arXiv preprint

2019

Decentralized Approximate Newton Methods for Convex Optimization on Networked Systems

arXiv preprint

2017

Fenchel Dual Gradient Methods for Distributed Convex Optimization over Time-varying Networks

arXiv preprint

2016

Relaxed Connected Dominating Set Problem with Application to Secure Power Network Design

arXiv preprint

2015

Convergence analysis of approximate primal solutions in dual first-order methods

arXiv preprint

2013

A Distributed Algorithm for Solving Positive Definite Linear Equations over Networks with Membership Dynamics

arXiv preprint

2011

Zero-Gradient-Sum Algorithms for Distributed Convex Optimization: The Continuous-Time Case

arXiv preprint

2010

Gossip Algorithms for Convex Consensus Optimization over Networks

arXiv preprint

2010

Controlled Hopwise Averaging: Bandwidth/Energy-Efficient Asynchronous Distributed Averaging for Wireless Networks

arXiv preprint