23 citations · 38 across the 21 of their papers we have counts for
22 papers
Generating Logically Consistent Synthetic Supply Chain Data with LLM-Driven Knowledge Graph Reasoning
Yunbo Long, Ge Zheng, Liming Xu +1
Synthetic data offers a promising solution to two persistent barriers in supply chain analytics: data scarcity and data privacy. However, for synthetic data to support operational…
EmoDistill: Offline Emotion Skill Distillation for Language Model Agents in Adversarial Negotiation
Yunbo Long, Haolang Zhao, Lukas Beckenbauer +2
Post-trained LLMs are often optimized to produce helpful, polite, and accommodating responses. In adversarial negotiation, however, such behavior can become a vulnerability: emotio…
Structural Consequences of Policy-Based Interventions on the Global Supply Chain Network
Lea Karbevska, Liming Xu, Zehui Dai +2
As global political tensions rise and the anticipation of additional tariffs from the United States on international trade increases, the issues of economic independence and supply…
EmoMAS: Emotion-Aware Multi-Agent System for High-Stakes Edge-Deployable Negotiation with Bayesian Orchestration
Yunbo Long, Yuhan Liu, Liming Xu
Large language models (LLMs) has been widely used for automated negotiation, but their high computational cost and privacy risks limit deployment in privacy-sensitive, on-device se…
Modelling viable supply networks with cooperative adaptive financing
Yaniv Proselkov, Liming Xu, Alexandra Brintrup
We propose a financial liquidity policy sharing method for firm-to-firm supply networks, introducing a scalable autonomous control function for viable complex adaptive supply netwo…
Automating Supply Chain Disruption Monitoring via an Agentic AI Approach
Sara AlMahri, Liming Xu, Alexandra Brintrup
Modern supply chains are increasingly exposed to disruptions from geopolitical events, demand shocks, trade restrictions, to natural disasters. While many of these disruptions orig…
EvoEmo: Towards Evolved Emotional Policies for Adversarial LLM Agents in Multi-Turn Price Negotiation
Yunbo Long, Liming Xu, Lukas Beckenbauer +2
Recent research on Chain-of-Thought (CoT) reasoning in Large Language Models (LLMs) has demonstrated that agents can engage in \textit{complex}, \textit{multi-turn} negotiations, o…
SynDelay: A Synthetic Dataset for Delivery Delay Prediction
Liming Xu, Yunbo Long, Alexandra Brintrup
Artificial intelligence (AI) is transforming supply chain management, yet progress in predictive tasks -- such as delivery delay prediction -- remains constrained by the scarcity o…
PA-CFL: Privacy-Adaptive Clustered Federated Learning for Transformer-Based Sales Forecasting on Heterogeneous Retail Data
Yunbo Long, Liming Xu, Ge Zheng +1
Federated learning (FL) enables retailers to share model parameters for demand forecasting while maintaining privacy. However, heterogeneous data across diverse regions, driven by…
Efficient and Privacy-Preserved Link Prediction via Condensed Graphs
Yunbo Long, Liming Xu, Alexandra Brintrup
Link prediction is crucial for uncovering hidden connections within complex networks, enabling applications such as identifying potential customers and products. However, this rese…
EmoDebt: Bayesian-Optimized Emotional Intelligence for Strategic Agent-to-Agent Debt Recovery
Yunbo Long, Yuhan Liu, Liming Xu +1
The emergence of autonomous Large Language Model (LLM) agents has created a new ecosystem of strategic, agent-to-agent interactions. However, a critical challenge remains unaddress…
TuneNSearch: a hybrid transfer learning and local search approach for solving vehicle routing problems
Arthur Corrêa, Cristóvão Silva, Liming Xu +2
This paper introduces TuneNSearch, a hybrid transfer learning and local search approach for addressing diverse variants of the vehicle routing problem (VRP). Our method uses reinfo…
LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion
Yunbo Long, Liming Xu, Alexandra Brintrup
Synthetic tabular data are increasingly being used to replace real data, serving as an effective solution that simultaneously protects privacy and addresses data scarcity. However,…
Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation
Yunbo Long, Liming Xu, Alexandra Brintrup
Current evaluations of synthetic tabular data mainly focus on how well joint distributions are modeled, often overlooking the assessment of their effectiveness in preserving realis…
Random Walk Guided Hyperbolic Graph Distillation
Yunbo Long, Liming Xu, Stefan Schoepf +1
Graph distillation (GD) is an effective approach to extract useful information from large-scale network structures. However, existing methods, which operate in Euclidean space to g…
Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models
Sara AlMahri, Liming Xu, Alexandra Brintrup
In today's globalized economy, comprehensive supply chain visibility is crucial for effective risk management. Achieving visibility remains a significant challenge due to limited i…
Towards Autonomous Supply Chains: Definition, Characteristics, Conceptual Framework, and Autonomy Levels
Liming Xu, Stephen Mak, Yaniv Proselkov +1
Recent global disruptions, such as the pandemic and geopolitical conflicts, have profoundly exposed vulnerabilities in traditional supply chains, requiring exploration of more resi…
Fair collaborative vehicle routing: A deep multi-agent reinforcement learning approach
Stephen Mak, Liming Xu, Tim Pearce +2
Collaborative vehicle routing occurs when carriers collaborate through sharing their transportation requests and performing transportation requests on behalf of each other. This ac…
Coalitional Bargaining via Reinforcement Learning: An Application to Collaborative Vehicle Routing
Stephen Mak, Liming Xu, Tim Pearce +2
Collaborative Vehicle Routing is where delivery companies cooperate by sharing their delivery information and performing delivery requests on behalf of each other. This achieves ec…
On Implementing Autonomous Supply Chains: a Multi-Agent System Approach
Liming Xu, Stephen Mak, Maria Minaricova +1
Trade restrictions, the COVID-19 pandemic, and geopolitical conflicts have significantly exposed vulnerabilities within traditional global supply chains. These events underscore th…
Implementation of Autonomous Supply Chains for Digital Twinning: a Multi-Agent Approach
Liming Xu, Yaniv Proselkov, Stefan Schoepf +3
Trade disruptions, the pandemic, and the Ukraine war over the past years have adversely affected global supply chains, revealing their vulnerability. Autonomous supply chains are a…
Multi-Agent Digital Twinning for Collaborative Logistics: Framework and Implementation
Liming Xu, Stephen Mak, Stefan Schoepf +2
Collaborative logistics has been widely recognised as an effective avenue to reduce carbon emissions by enhanced truck utilisation and reduced travel distance. However, stakeholder…