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Position: Key Claims in LLM Research Have a Long Tail of Footnotes

Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-review

Open access

Publication Information

Output type

Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 42647-42665

Journal (Volume, Issue Number)

Proceedings of the 41st International Conference on Machine Learning (Volume 235)

Publication milestones

  • Published - 2024

Publication status

Published - 2024

Publication IDs

  • Scopus: 85203792915

Abstract

Much of the recent discourse within the ML community has been centered around Large Language Models (LLMs), their functionality and potential – yet not only do we not have a working definition of LLMs, but much of this discourse relies on claims and assumptions that are worth re-examining. We contribute a definition of LLMs, critically examine five common claims regarding their properties (including ’emergent properties’), and conclude with suggestions for future research directions and their framing.

Publication metrics

PlumX

Citations
6
Captures
16

Funding Details

DFF Inge Lehmann grant to Anna Rogers (3160-00022B)
FundersFunding numbers
-
-

Related Event

Title

International Conference on Machine Learning

Event type

Conference

Degree of recognition

International event

Date

21/07/2024 - 27/07/2024

Location

Wien Exhibition Congress CenterViennaAustria