Byte-based Multilingual NMT for Endangered Languages

Proceedings of the 29th International Conference on Computational Linguistics, pages 471–484 October 12–17, 2022. 471 CorefDiffs: Co-referential and Differential Knowledge Flow in Document Grounded Conversations Lin Xu1, Qixian Zhou2, Jinlan Fu1, Min-Yen Kan1, See-Kiong Ng1 1National University of Singapore, 2ByteDance {cathyxl2016,qixianzhou.mail,jinlanjonna}@gmail.com {knmnyn,seekiong}@nus.edu.sg Abstract Knowledge-grounded dialog systems need to incorporate smooth transitions among knowl- edge selected for generating responses, to en- sure that dialog flows naturally. For document- grounded dialog systems, the inter- and intra- document knowledge relations can be used to model such conversational flows. We develop a novel Multi-Document Co-Referential Graph (Coref-MDG) to effectively capture the inter- document relationships based on common- sense and similarity and the intra-document co- referential structures of knowledge segments within the grounding documents. We propose CorefDiffs, a Co-referential and Differential flow management method, to linearize the static Coref-MDG into conversational sequence logic. CorefDiffs performs knowledge selection by accounting for contextual graph structures and the knowledge difference sequences. CorefD- iffs significantly outperforms the state-of-the- art by 9.5%, 7.4% and 8.2% on three public benchmarks. This demonstrates that the effec- tive modeling of co-reference and knowledge difference for dialog flows are critical for tran- sitions in document-grounded conversation1. 1 Introduction Document-grounded conversations (Moghe et al., 2018; Dinan et al., 2018; Feng et al., 2021b) is a core class of knowledge-grounded dialogs that leverage text-based knowledge segments from doc- uments to generate informative dialog responses. This task is typically divided into two sub-tasks, given the dialog history (Dinan et al., 2018): namely, knowledge selection and response genera- tion. Knowledge selection, which determines the content of the generated responses (Moghe et al., 2018; Dinan et al., 2018), is the crucial sub-task for dialog flow management as it leads to the manifes- tation of knowledge transition (Meng et al., 2020), essential for naturalistic engaging conversations. 1The source code has been released at https://github.com/ cathyxl/coref-diffs Science fiction film The empire strikes back sent-1 Star wars (film) sent-1 sent-2 part_of overlap genre_of genre_of Science fiction film uses speculative, fictional science ... Star wars is a 1977... space opera film It depicts the adventures of ...in a galaxy Star wars (film) starring mark hamill, harrison ford The empire strikes back is a 1980...film. sent-3 co-ref co-ref co-ref Coref-MDG 1 2 3 4 Conversation: Usr1: I like science fiction Bot1: yes. i like movies that use speculative, fictional science...depictions [Science fiction film, sent-1] Usr2: I liked the star wars movies and the alien ... Bot2: I wish i was able to see star wars in 1977. [Star wars (film), sent-1] Usr3: I loved the tv series. Bot3: I prefer the film that stars mark hamill and harrison ford.[Star wars (film), sent-3] Usr4: I like that one too. the first sci fi film was... Bot4: Cool. Did you ever see the empire strikes back in 1980? ... [The empire strikes back, 1] Topic node Knowledge node 1 2 3 4 sent-1 Documents Figure 1: Co-Referential Multi-Document Graph (Coref-MDG). Topic vertices correspond to documents and are connected by commonsense/word overlap rela- tions. Knowledge vertices are …

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