mlsanityData to 14 Oct 2026

Evaluator for Emotionally Consistent Chatbots

arXiv 2112.01616 ↗First posted 2 Dec 2021cs.CL cs.AIcited by 1

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Abstract (arXiv)

One challenge for evaluating current sequence- or dialogue-level chatbots, such as Empathetic Open-domain Conversation Models, is to determine whether the chatbot performs in an emotionally consistent way. The most recent work only evaluates on the aspects of context coherence, language fluency, response diversity, or logical self-consistency between dialogues. This work proposes training an evaluator to determine the emotional consistency of chatbots.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 3 of its 5 references that are in the map. First posted on arXiv 2 Dec 2021.

Builds on

3 of 5 references.

References · 3

  1. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  2. 2017DailyDialog: A Manually Labelled Multi-turn Dialogue Datasetcited by 652
  3. 2017Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memorycited by 167

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