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Found 3 papers, 1 papers with code
Exploiting the Potential of Seq2Seq Models as Robust Few-Shot Learners
In-context learning, which offers substantial advantages over fine-tuning, is predominantly observed in decoder-only models, while encoder-decoder (i. e., seq2seq) models excel in methods that rely on weight updates.
On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model
Many recent studies on large-scale language models have reported successful in-context zero- and few-shot learning ability.
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers
GPT-3 shows remarkable in-context learning ability of large-scale language models (LMs) trained on hundreds of billion scale data.
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