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researcher

J. Sevilla

7 papers hereh-index 81.3k citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author4
  • last author2

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.AI1
  • cs.CL1
  • econ.GN1
same name
  • J. Sevilla — 4 papers, h 10
  • J. Sevilla — 1 paper, h 4
  • J. Sevilla — 1 paper, h 3
  • J. Sevilla — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20222025
most citedCompute Trends Across Three Eras of Machine Learning

312 citations · 445 across the 7 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023

Power Law Trends in Speedrunning and Machine Learning

Ege Erdil, Jaime Sevilla

We find that improvements in speedrunning world records follow a power law pattern. Using this observation, we answer an outstanding question from previous work: How do we improve…

cs.LG2022★ 82 cited

Will we run out of data? Limits of LLM scaling based on human-generated data

Pablo Villalobos, Anson Ho, Jaime Sevilla +3

We investigate the potential constraints on LLM scaling posed by the availability of public human-generated text data. We forecast the growing demand for training data based on cur…

cs.LG2022★ 29 cited

Machine Learning Model Sizes and the Parameter Gap

Pablo Villalobos, Jaime Sevilla, Tamay Besiroglu +3

We study trends in model size of notable machine learning systems over time using a curated dataset. From 1950 to 2018, model size in language models increased steadily by seven or…

cs.LG2022★ 312 cited

Compute Trends Across Three Eras of Machine Learning

Jaime Sevilla, Lennart Heim, Anson Ho +3

Compute, data, and algorithmic advances are the three fundamental factors that guide the progress of modern Machine Learning (ML). In this paper we study trends in the most readily…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.