Genteel-Negotiator: LLM-enhanced mixture-of-expert-based reinforcement learning approach for polite negotiation dialogue by Dr. Mauajama Firdaus

Venue: SIT001

Abstract : Developing intelligent negotiation dialogue systems that promote fair and sustainable outcomes is crucial for advancing automated negotiation for social good. Since effective negotiation requires balancing cooperation and competition while maintaining respect, we propose GENTEEL-NEGOTIATOR, a polite negotiation dialogue system for tourism and e-commerce domains. We introduce NEGOCHAT, a tourism negotiation dataset, and enrich it along with the Integrative Negotiation Dataset (IND) using diverse negotiation strategies. Built on an LLM-enhanced Mixture-of-Experts reinforcement learning framework, the model incorporates dedicated experts for negotiation, politeness, and coherence, guided by a reward function capturing strategy alignment, politeness, coherence, and engagingness. Extensive automatic and human evaluations demonstrate its effectiveness in generating polite, coherent, and goal-oriented negotiation responses.

Bio: Dr. Mauajama Firdaus is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology (ISM) Dhanbad. She completed her Ph.D. in Computer Science & Engineering from IIT Patna and pursued postdoctoral research at the University of Alberta, Canada. Her research expertise lies in Natural Language Processing, Multimodal and Multilingual AI, Dialogue Systems, Explainable AI, and Affective Computing. Her work focuses on building empathetic, polite, and emotion-aware conversational AI systems, with applications in social good, mental health, customer care, and multilingual settings. She has published extensively in top-tier journals and conferences including IEEE, ACM, AAAI, ACL, EMNLP, and Information Fusion, and holds a US patent in spoken language understanding. She also serves as Associate Editor for reputed international journals published by Elsevier.