arXiv:2608. 12062v1 Announce Type: cross Abstract: Developing dialogue systems capable of engaging in multi-turn, goal-oriented conversations remains a significant challenge, especially in specialized domains with limited data.
By Lior Baruch, Moshe Butman, Kfir Bar, Doron Friedman
arXiv:2607. 00010v1 Announce Type: cross Abstract: Conversational recommender systems (CRSs) are a core component of next-generation intelligent recommender systems because they enable users to actively elicit preferences, clarify intentions, and adapt recommendations in real time.
By Nipun B Nair, Tongtong Wu, Weiqing Wang
arXiv:2608. 13833v1 Announce Type: cross Abstract: Conversational advertising aims to deliver useful ads within multi-turn assistant interactions.
By Simiao Zuo, Chenhui Xu, Yimeng Jia, Qiang Lou, Jian Jiao, Denis Charles
arXiv:2608. 06329v1 Announce Type: cross Abstract: Task-oriented conversational agents are evaluated using curated or automatically generated benchmarks, yet benchmark quality is rarely assessed.
By Noam Koren, Roy Bar-Haim, Abigail Goldsteen
arXiv:2606. 13683v1 Announce Type: new Abstract: To address the challenge that current dialogue policy planning methods struggle to dynamically adapt to diverse user characteristics, this paper proposes a User Portrait based Nested Rollout Policy Adaptation (UP-NRPA) online framework with Large Language Models.
By Hui Wang, Fafa Zhang, Meng Liu, Xiangyu Chen, Chaoxu Mu
arXiv:2606. 11070v1 Announce Type: cross Abstract: Recent advances in reasoning and tool-calling capabilities of large language models (LLMs) have enabled increasingly capable agentic systems.
By Genta Indra Winata, Amartya Chakraborty, Yuzhen Lin, Swasthi P Rao, Shikhhar Siingh, Houhan Lu, Nadia Bathaee, Sriharsha Hatwar, Paresh Dashore, Anmol Jain, Kshitij Tayal, Xiuzhu Lin, Anirban Das, Sambit Sahu, Shi-Xiong Zhang