Jordan Hoffmann
6 papers · 2019–2022 · 4 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (15) π Cross-Pollinator (15) π Interdisciplinary Bridge π Conference Polyglot (4) π§ Keyword Pioneer
π£
Hot Topic Early Bird
π₯
Mega-Team
(28)
Conferences
ICML (2)
NIPS (2)
EMNLP (1)
ICLR (1)
Top co-authors
Keywords
scaling law
(2)
large language model
(2)
variational inference
(1)
natural language processing
(1)
graph analysis
(1)
question answering
(1)
commonsense knowledge
(1)
document retrieval
(1)
community detection
(1)
probabilistic generative model
(1)
mixture of expert
(1)
model scaling
(1)
pre-trained language model
(1)
parameter efficiency
(1)
token scaling
(1)
knowledge-intensive task
(1)
node representation learning
(1)
routing network
(1)
retrieval-augmented language model
(1)
transformer model
(1)
Papers
An empirical analysis of compute-optimal large language model training
NIPS 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
NIPS 2019