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WeChat AI & ICT's Submission for DSTC9 Interactive Dialogue Evaluation Track

arXiv 2101.07947 ↗First posted 20 Jan 2021cs.CL cs.AIcited by 0

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Abstract (arXiv)

We participate in the DSTC9 Interactive Dialogue Evaluation Track (Gunasekara et al. 2020) sub-task 1 (Knowledge Grounded Dialogue) and sub-task 2 (Interactive Dialogue). In sub-task 1, we employ a pre-trained language model to generate topic-related responses and propose a response ensemble method for response selection. In sub-task2, we propose a novel Dialogue Planning Model (DPM) to capture conversation flow in the interaction with humans. We also design an integrated open-domain dialogue system containing pre-process, dialogue model, scoring model, and post-process, which can generate fluent, coherent, consistent, and humanlike responses. We tie 1st on human ratings and also get the highest Meteor, and Bert-score in sub-task 1, and rank 3rd on interactive human evaluation in sub-task 2.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 21 of its 29 references that are in the map. First posted on arXiv 20 Jan 2021.

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21 of 29 references.

References · 21

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9 more
  1. 2020Sequential Latent Knowledge Selection for Knowledge-Grounded Dialoguecited by 82
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