What is recorded here?
Trained GPT-2 as a large autoregressive transformer on WebText and documented zero-shot transfer to several language tasks without task-specific fine-tuning.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The 2019 paper reports task- and setup-specific zero-shot results; it is distinct from GPT-1 and GPT-3 and does not show general reasoning reliability.
Read the original work
- Radford and colleagues: GPT-2 and unsupervised multitask language modeling — original paper
- Radford and colleagues: GPT-2 and unsupervised multitask language modeling — company research page
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Alec Radford; Jeffrey Wu; Rewon Child; David Luan; Dario Amodei; Ilya Sutskever
Complete named paper byline. Human research, source-reported system execution and experimental validation are distinct; individual effort shares are not measured.
Research locations and affiliations
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English catalogue narrative
Radford and colleagues: GPT-2 and unsupervised multitask language modeling
Trained GPT-2 as a large autoregressive transformer on WebText and documented zero-shot transfer to several language tasks without task-specific fine-tuning.
Scientific scope
The 2019 paper reports task- and setup-specific zero-shot results; it is distinct from GPT-1 and GPT-3 and does not show general reasoning reliability.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Alec Radford; Jeffrey Wu; Rewon Child; David Luan; Dario Amodei; Ilya Sutskever
Complete named paper byline. Human research, source-reported system execution and experimental validation are distinct; individual effort shares are not measured.