mlsanityData to 7 Oct 2026

BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage

arXiv 2208.03188 ↗First posted 5 Aug 2022cs.CL cs.AIcited by 197

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Cited by 23 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We present BlenderBot 3, a 175B parameter dialogue model capable of open-domain conversation with access to the internet and a long-term memory, and having been trained on a large number of user defined tasks. We release both the model weights and code, and have also deployed the model on a public web page to interact with organic users. This technical report describes how the model was built (architecture, model and training scheme), and details of its deployment, including safety mechanisms. Human evaluations show its superiority to existing open-domain dialogue agents, including its predecessors (Roller et al., 2021; Komeili et al., 2022). Finally, we detail our plan for continual learning using the data collected from deployment, which will also be publicly released. The goal of this research program is thus to enable the community to study ever-improving responsible agents that learn through interaction.

Key facts. Cited by 197 papers in the map (data through 7 Oct 2026). Builds on 78 of its 111 references that are in the map. First posted on arXiv 5 Aug 2022.

Builds on

78 of 111 references.

References · 78

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50 most cited of 78 All 78 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 14; 2023: 105; 2024: 36; 2025: 28; 2026: 14.

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50 most cited of 197 All 197 (JSON)