Shared Task:

Persona Grounded Dialogue

This year we have partnered with collaborators at Sony and EPFL to be the official host for the two tasks for Peacock Shared Task.


Task 1 Commonsense Persona Grounded Dialogue Challenge (25,000 dollars in cash prize)

To sustain coherent and engaging conversations, dialogue agents must consider the personas of listeners to produce utterances that cater to their interests. They must also maintain consistent speaker personas, so that their counterparts feel engaged in a realistic conversation. However, achieving this persona alignment requires understanding the inter-connected interests, habits, experiences, and relationships of various real-word personas, and leveraging them effectively to robustly and believably engage in conversations. In this task, we are calling for dialogue response generation systems that can make good representation and incorporation of personas grounded on commonsense. We prepared a new persona-grounded dialogue dataset for the evaluation in open-domain dialogue, which was created based on a Persona Commonsense Knowledge (hereinafter PeaCok) Graph released at ACL2023. Each dialogue is a conversation between a pair of workers assigned a persona. Each persona consisted of several profile sentences including some personal information (e.g. name, age, etc.), head personas in PeaCok, and tail personas corresponding to the head personas picked out from PeaCok. The dialogues are consistent throughout because profile sentences are organized naturally related to each other based on the Knowledge Graph.

For details please refer to this page: Task 1 webpage. This is the link for the challenges Discord channel. 

Timeline

The challenge will take place across 3 Rounds which differ in the evaluation dataset used for ranking the systems.

🏆 Prizes


Task 2  Commonsense Persona Knowledge Linking (10,000 dollars in cash prize)

Understanding rich dialogues often requires NLP systems to access relevant commonsense persona knowledge that grounds the dialogue. However, it is challenging to retrieve such relevant persona commonsense from knowledge bases, due to the complex contexts of real-world dialogues, and the implicit and ambiguous nature of commonsense knowledge. In this task, we are calling for commonsense persona knowledge linkers that can robustly identify relevant commonsense facts associated with speakers and listeners in dialogues. 

For details please refer to this page: Task 2 webpage. This is the link for the challenges Discord channel. 

Timeline

The challenge will take place across 3 Rounds which differ in the evaluation dataset used for ranking the systems.

🏆 Prizes


If you have questions regarding shared tasks please contact us: nlp4convai-organizers@googlegroups.com  

This is the link for the challenges Discord channel.