collaborators

20 papers

cs.AI2026

Helicase: Uncertainty-Guided Supply Chain Knowledge Graph Construction with Autonomous Multi-Agent LLMs

Yunbo Long, Haolang Zhao, Ge Zheng +1

LLM-based multi-agent systems have been widely adopted for knowledge retrieval and report generation, synthesizing known information through web search and textual reasoning. Howev…

cs.CL2026

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…

cs.CL2026

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…

cs.AI2026

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…

cs.AI2026

VeriTrace: Evolving Mental Models for Deep Research Agents

Haolang Zhao, Yunbo Long, Lukas Beckenbauer +1

Deep research agents face vast, interdependent, and pervasively uncertain information. Existing systems explore what evolving intermediate representations should look like, but lea…

cs.MA2026

Self-Evolving Multi-Agent Systems via Decentralized Memory

Guangya Hao, Yunbo Long, Zhuokai Zhao

Self-evolving multi-agent systems (MAS) have emerged as a promising route to LLM agents that continually improve from experience, with persistent memory at their foundation. Howeve…