On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers

Research article (Findings of the Association for Computational Linguistics: EMNLP 2020, 2020) · cited 15× · AI/ML
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On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers

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On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers. Retrieved May 24, 2026, from https://4ort.xyz/entity/on-the-interplay-between-fine-tuning-and-sentence-level-probing-for-linguistic-knowledge-in-pre-trained-transformers
MLA “On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/on-the-interplay-between-fine-tuning-and-sentence-level-probing-for-linguistic-knowledge-in-pre-trained-transformers.
BibTeX @misc{4ortxyz_on-the-interplay-between-fine-tuning-and-sentence-level-probing-for-linguistic-knowledge-in-pre-trained-transformers_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers}}, year = {2026}, url = {https://4ort.xyz/entity/on-the-interplay-between-fine-tuning-and-sentence-level-probing-for-linguistic-knowledge-in-pre-trained-transformers}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers — https://4ort.xyz/entity/on-the-interplay-between-fine-tuning-and-sentence-level-probing-for-linguistic-knowledge-in-pre-trained-transformers (retrieved 2026-05-24)

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