activity
20182026
most citedNeural Text Generation with Unlikelihood Training

241 citations · 377 across the 27 of their papers we have counts for

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5 papers · 1 filter

cs.AI2024

The Llama 3 Herd of Models

Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models th…

cs.AI20208 cited

Deploying Lifelong Open-Domain Dialogue Learning

Kurt Shuster, Jack Urbanek, Emily Dinan +2

Much of NLP research has focused on crowdsourced static datasets and the supervised learning paradigm of training once and then evaluating test performance. As argued in de Vries e…

cs.AI20208 cited

I love your chain mail! Making knights smile in a fantasy game world: Open-domain goal-oriented dialogue agents

Shrimai Prabhumoye, Margaret Li, Jack Urbanek +4

Dialogue research tends to distinguish between chit-chat and goal-oriented tasks. While the former is arguably more naturalistic and has a wider use of language, the latter has cle…

cs.AI20193 cited

Generating Interactive Worlds with Text

Angela Fan, Jack Urbanek, Pratik Ringshia +8

Procedurally generating cohesive and interesting game environments is challenging and time-consuming. In order for the relationships between the game elements to be natural, common…

cs.AI20197 cited

The Second Conversational Intelligence Challenge (ConvAI2)

Emily Dinan, Varvara Logacheva, Valentin Malykh +14

We describe the setting and results of the ConvAI2 NeurIPS competition that aims to further the state-of-the-art in open-domain chatbots. Some key takeaways from the competition ar…