The Dialogue Dodecathlon: Open-Domain Knowledge and Image Grounded Conversational Agents
Kurt Shuster, Da Ju, Stephen Roller, Emily Dinan, Y-Lan Boureau, Jason Weston
Abstract
We introduce dodecaDialogue: a set of 12 tasks that measures if a conversational agent can communicate engagingly with personality and empathy, ask questions, answer questions by utilizing knowledge resources, discuss topics and situations, and perceive and converse about images. By multi-tasking on such a broad large-scale set of data, we hope to both move towards and measure progress in producing a single unified agent that can perceive, reason and converse with humans in an open-domain setting. We show that such multi-tasking improves over a BERT pre-trained baseline, largely due to multi-tasking with very large dialogue datasets in a similar domain, and that the multi-tasking in general provides gains to both text and image-based tasks using several metrics in both the fine-tune and task transfer settings. We obtain state-of-the-art results on many of the tasks, providing a strong baseline for this challenge.- Anthology ID:
- 2020.acl-main.222
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2453–2470
- Language:
- URL:
- https://aclanthology.org/2020.acl-main.222
- DOI:
- 10.18653/v1/2020.acl-main.222
- Cite (ACL):
- Kurt Shuster, Da Ju, Stephen Roller, Emily Dinan, Y-Lan Boureau, and Jason Weston. 2020. The Dialogue Dodecathlon: Open-Domain Knowledge and Image Grounded Conversational Agents. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2453–2470, Online. Association for Computational Linguistics.
- Cite (Informal):
- The Dialogue Dodecathlon: Open-Domain Knowledge and Image Grounded Conversational Agents (Shuster et al., ACL 2020)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2020.acl-main.222.pdf
- Data
- ConvAI2, DailyDialog, ELI5, Wizard of Wikipedia