Dec 21, 2022 · This paper proposes prompt-augmented linear probing (PALP), a hybrid of linear probing and ICL, which leverages the best of both worlds.
This paper proposes prompt-augmented linear probing (PALP), a hybrid of linear probing and ICL, which leverages the best of both worlds.
Feb 7, 2023 · Through in-context learning (ICL), large-scale language models are effective few-shot learners without additional model fine-tuning.
Dec 21, 2022 · Through in-context learning (ICL), large-scale language models are effective few-shot learners without additional model fine-tuning.
Through in-context learning (ICL), large-scale language models are effective few-shot learners without additional model fine-tuning.
People also ask
What is linear probing vs transfer learning?
What is linear probing in ML?
Co-authors ; Prompt-augmented linear probing: Scaling beyond the limit of few-shot in-context learners. H Cho, HJ Kim, J Kim, SW Lee, S Lee, KM Yoo, T Kim.
Prompt-Augmented Linear Probing: Scaling Beyond The Limit of Few-shot In-Context Learners （2022.12.21）. Hyunsoo Cho, Hyuhng Joon Kim, Junyeob Kim, Sang-Woo ...
공동 저자 ; Prompt-augmented linear probing: Scaling beyond the limit of few-shot in-context learners. H Cho, HJ Kim, J Kim, SW Lee, S Lee, KM Yoo, T Kim.
Through in-context learning (ICL), large-scale language models are effective few-shot learners without additional model fine-tuning. In-Context Learning ...
Prompt-Augmented Linear Probing: Scaling Beyond the Limit of Few-shot In-Context Learner. Hyunsoo Cho, Hyuhng Joon Kim, Junyeob Kim, Sang-Woo Lee, Sang-goo ...