The noetic end-to-end response selection challenge as one track in Dialog System Technology Challenges 7 (DSTC7) aims to push the state of the art of utterance classification for real world goal-oriented dialog systems, for which participants need to select the correct next utterances from a set of candidates for the multi-turn context. This paper describes our systems that are ranked the top on both datasets under this challenge, one focused and small (Advising) and the other more diverse and large (Ubuntu). Previous state-of-the-art models use hierarchy-based (utterance-level and token-level) neural networks to explicitly model the interactions among different turns' utterances for context modeling. In this paper, we investigate a sequential matching model based only on chain sequence for multi-turn response selection. Our results demonstrate that the potentials of sequential matching approaches have not yet been fully exploited in the past for multi-turn response selection. In addition to ranking the top in the challenge, the proposed model outperforms all previous models, including state-of-the-art hierarchy-based models, and achieves new state-of-the-art performances on two large-scale public multi-turn response selection benchmark datasets.
Building Sequential Inference Models for End-to-End Response Selection
National Engineering Laboratory for Speech and Language Information ProcessingUniversity of Science and Technology of China（中国科学技术大学语音及语言信息处理国家工程实验室）；iFLYTEK Research（科大讯飞研究）
Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots
State Key Lab of Software Development Environment, Beihang University（北京航空航天大学软件开发环境国家重点实验室）；Microsoft Research（微软研究院）；College of Computer and Control Engineering, Nankai University（南开大学计算机与控制工程学院）
From Myopic Selection to Long-Horizon Awareness: Sequential LLM Routing for Multi-Turn Dialogue
School of Computer Science, Shanghai Jiao Tong University, Shanghai, China（上海交通大学计算机科学学院）；WeChat, Tencent Inc, Beijing, China（腾讯北京研发中心）；University at Buffalo, New York, United States（布法罗大学）
