Jordan Hoffmann
6 papers · 2019–2022 · 4 venues · across top CS/AI venues
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Achievements
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Conference Polyglot · Bronze
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Interdisciplinary Bridge · Bronze
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Taxonomy Completionist
(17)
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Hot Topic Early Bird
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Mega-Team · Squad
Venues
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Research topics
Machine Learning
(5)
Natural Language Processing
(4)
Deep Learning
(3)
Resources & Methods
(3)
Architectures
(2)
Learning Types
(2)
Models
(2)
Optimization & Theory · Machine Learning
(2)
Artificial Intelligence
(1)
Application Areas
(1)
Applications
(1)
Core AI
(1)
Core Methods
(1)
Generation
(1)
Optimization & Theory · Deep Learning
(1)
Keywords
scaling law
(2)
large language model
(2)
variational inference
(1)
natural language processing
(1)
graph analysis
(1)
attention mechanism
(1)
question answering
(1)
commonsense knowledge
(1)
document retrieval
(1)
community detection
(1)
probabilistic generative model
(1)
recurrent neural network
(1)
mixture of expert
(1)
model scaling
(1)
pre-trained language model
(1)
parameter efficiency
(1)
token scaling
(1)
knowledge-intensive task
(1)
modular structure
(1)
node representation learning
(1)
Papers
An empirical analysis of compute-optimal large language model training
NeurIPS 2022
A Systematic Investigation of Commonsense Knowledge in Large Language Models
EMNLP 2022
Improving Language Models by Retrieving from Trillions of Tokens
ICML 2022
Unified Scaling Laws for Routed Language Models
ICML 2022
Recurrent Independent Mechanisms
ICLR 2021
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
NeurIPS 2019