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- Deep language algorithms predict semantic comprehension from brain activity https://www.nature.com/articles/s41598-022-20460-9 46 comments
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Linked pages
- [2005.14165] Language Models are Few-Shot Learners https://arxiv.org/abs/2005.14165 201 comments
- Creative Commons — Attribution 4.0 International — CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ 95 comments
- GPT-2 and the Nature of Intelligence https://thegradient.pub/gpt2-and-the-nature-of-intelligence/ 56 comments
- [1810.04805] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding https://arxiv.org/abs/1810.04805 25 comments
- [1906.08237] XLNet: Generalized Autoregressive Pretraining for Language Understanding https://arxiv.org/abs/1906.08237 15 comments
- https://www.pnas.org/doi/10.1073/pnas.2105646118#fig02 4 comments
- [2111.14232] Long-range and hierarchical language predictions in brains and algorithms https://arxiv.org/abs/2111.14232 2 comments
- [2103.06332] Hurdles to Progress in Long-form Question Answering https://arxiv.org/abs/2103.06332 1 comment
- [1910.10683] Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer https://arxiv.org/abs/1910.10683 1 comment
- [2102.12092] Zero-Shot Text-to-Image Generation https://arxiv.org/abs/2102.12092 0 comments
- Gentle https://lowerquality.com/gentle/ 0 comments
- [1910.14599] Adversarial NLI: A New Benchmark for Natural Language Understanding https://arxiv.org/abs/1910.14599 0 comments
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