What is recorded here?
Developed general-domain LM pretraining, target-domain adaptation and classifier fine-tuning using discriminative layerwise rates, slanted triangular schedules, gradual unfreezing and pooled recurrent states.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Januaryv1 is FitLaM with five datasets; finalACL paper is ULMFiT with six, retained as one contribution rather than two methods. Inherits LM fine-tuning, AWD-LSTM, triangular rates and chain-thaw-style gradual adaptation. Universal names practical reuse criteria, not proof for every NLP task or100fold universal sample efficiency; pretraining and tuning costs remain.
Read the original work
- Fine-tuned Language Models for Text Classification
- Universal Language Model Fine-tuning for Text Classification
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People and systems
Jeremy Howard; Sebastian Ruder
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
FitLaM / ULMFiT: practical language-model fine-tuning for text classification
Developed general-domain LM pretraining, target-domain adaptation and classifier fine-tuning using discriminative layerwise rates, slanted triangular schedules, gradual unfreezing and pooled recurrent states.
Scientific scope
Januaryv1 is FitLaM with five datasets; finalACL paper is ULMFiT with six, retained as one contribution rather than two methods. Inherits LM fine-tuning, AWD-LSTM, triangular rates and chain-thaw-style gradual adaptation. Universal names practical reuse criteria, not proof for every NLP task or100fold universal sample efficiency; pretraining and tuning costs remain.
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
Jeremy Howard; Sebastian Ruder
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.