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.
| Originalsprog | Engelsk |
|---|---|
| Konferencepublikationer | Proceedings of the 41st International Conference on Machine Learning |
| Vol/bind | 235 |
| Sider (fra-til) | 42647-42665 |
| Status | Udgivet - 2024 |
| Begivenhed | International Conference on Machine Learning - Wien Exhibition Congress Center, Vienna, Østrig Varighed: 21 jul. 2024 → 27 jul. 2024 https://icml.cc/Conferences/2024 |
Konference
| Konference | International Conference on Machine Learning |
|---|---|
| Lokation | Wien Exhibition Congress Center |
| Land/Område | Østrig |
| By | Vienna |
| Periode | 21/07/2024 → 27/07/2024 |
| Internetadresse |
Emneord
- NLP
- language models
Fingeraftryk
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