Papers: Difference between revisions
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'''[[An Image is Worth 16x16 Words]]''' - https://arxiv.org/abs/2010.11929 - Transformers for Image Recognition at Scale - [[Vision Transformer]] ([[ViT]]) | '''[[An Image is Worth 16x16 Words]]''' - https://arxiv.org/abs/2010.11929 - Transformers for Image Recognition at Scale - [[Vision Transformer]] ([[ViT]]) | ||
'''[[Block-Recurrent Transformers]]''' - https://arxiv.org/abs/2203.07852 | |||
'''[[Language Models are Few-Shot Learners]]''' - https://arxiv.org/abs/2005.14165 - [[GPT]] | '''[[Language Models are Few-Shot Learners]]''' - https://arxiv.org/abs/2005.14165 - [[GPT]] | ||
Revision as of 17:49, 5 February 2023
https://arxiv.org/abs/2301.13779 (FLAME: A small language model for spreadsheet formulas) - Small model specifically for spreadsheets by Miscrofot
Attention Is All You Need - https://arxiv.org/abs/1706.03762 - - influential paper that introduced Transformer
An Image is Worth 16x16 Words - https://arxiv.org/abs/2010.11929 - Transformers for Image Recognition at Scale - Vision Transformer (ViT)
Block-Recurrent Transformers - https://arxiv.org/abs/2203.07852
Language Models are Few-Shot Learners - https://arxiv.org/abs/2005.14165 - GPT
Memorizing Transformers - https://arxiv.org/abs/2203.08913 -
OpenAI CLIP - https://arxiv.org/abs/2103.00020, https://openai.com/blog/clip/ - Learning Transferable Visual Models From Natural Language Supervision
Transformer-XL - https://arxiv.org/abs/1901.02860 - Attentive Language Models Beyond a Fixed-Length Context