4 papers
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…
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…
Orchestrator: Active Inference for Multi-Agent Systems in Long-Horizon Tasks
Lukas Beckenbauer, Johannes-Lucas Loewe, Ge Zheng +1
Complex, non-linear tasks challenge LLM-enhanced multi-agent systems (MAS) due to partial observability and suboptimal coordination. We propose Orchestrator, a novel MAS framework…