16 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 align responses with human preferences, making them safe, polite, and conversationally appropriate. In adversarial negotiation, however, th…
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…
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…
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…