Methods › Natural Language Processing › Open-Domain Chatbots › Meena

Meena

3 papers tagged archive 2025-07-28

Introduced by Daniel Adiwardana et al. in Towards a Human-like Open-Domain Chatbot

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Meena is a multi-turn open-domain chatbot trained end-to-end on data mined and filtered from public domain social media conversations. This 2.6B parameter neural network is simply trained to minimize perplexity of the next token. A seq2seq model is used with the Evolved Transformer as the main architecture. The model is trained on multi-turn conversations where the input sequence is all turns of the context and the output sequence is the response.

PaperSource

Papers archive 2025-07-28

3 shown of 3, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

4 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Chatbot2
Neural Architecture Search1
Scheduling1
Specificity1

Usage over time archive 2025-07-28

Papers per year tagged with Meena: 2020 to 2022, peak 1 1 0 2020: 1 paper 2020 2021: 1 paper 2021 2022: 1 paper 2022
Papers per year the archive tags with this method, by the paper's archive date (3 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Open-Domain ChatbotsConversational Models

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections