# The Wizard of Curiosities: Enriching Dialogues with Fun Facts

arXiv: https://arxiv.org/abs/2309.11283 · HTML: https://mlsanity.com/paper/2309.11283/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 15 references that are in the map.
- First posted on arXiv 20 Sep 2023.

## Builds on (most cited first, 10 of 10)

- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven Exploration](https://mlsanity.com/paper/2002.09253/) (2020)
- [Episodic Multi-agent Reinforcement Learning with Curiosity-Driven Exploration](https://mlsanity.com/paper/2111.11032/) (2021)
- [See, Hear, Explore: Curiosity via Audio-Visual Association](https://mlsanity.com/paper/2007.03669/) (2020)
- [Alexa, Let's Work Together: Introducing the First Alexa Prize TaskBot Challenge on Conversational Task Assistance](https://mlsanity.com/paper/2209.06321/) (2022)
- [Alquist 4.0: Towards Social Intelligence Using Generative Models and Dialogue Personalization](https://mlsanity.com/paper/2109.07968/) (2021)
- [Task Conditioned BERT for Joint Intent Detection and Slot-filling](https://mlsanity.com/paper/2308.06165/) (2023)
- [Open-Domain Conversational Search Assistant with Transformers](https://mlsanity.com/paper/2101.08197/) (2021)

## Built on by (most cited first, 2 of 2)

- [TWIZ-v2: The Wizard of Multimodal Conversational-Stimulus](https://mlsanity.com/paper/2310.02118/) (2023)
- [Leveraging Interesting Facts to Enhance User Engagement with Conversational Interfaces](https://mlsanity.com/paper/2404.06659/) (2024)

## Abstract (arXiv)

Introducing curiosities in a conversation is a way to teach something new to the person in a pleasant and enjoyable way. Enriching dialogues with contextualized curiosities can improve the users' perception of a dialog system and their overall user experience. In this paper, we introduce a set of curated curiosities, targeting dialogues in the cooking and DIY domains. In particular, we use real human-agent conversations collected in the context of the Amazon Alexa TaskBot challenge, a multimodal and multi-turn conversational setting. According to an A/B test with over 1000 conversations, curiosities not only increase user engagement, but provide an average relative rating improvement of 9.7%.