I posted a list of papers on twitter, and will be posting a summary for each of them as well. here is the list https://twitter.com/vrungta/status/1623343807227105280

Unlocking the Secrets of AI: A Journey through the Foundational Papers by @vrungta (2023)

1. "Attention is All You Need" (2017) - https://arxiv.org/abs/1706.03762 (Google Brain) 2. "Generative Adversarial Networks" (2014) - https://arxiv.org/abs/1406.2661 (University of Montreal) 3. "Dynamic Routing Between Capsules" (2017) - https://arxiv.org/abs/1710.09829 (Google Brain) 4. "Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks" (2016) - https://arxiv.org/abs/1511.06434 (University of Montreal) 5. "ImageNet Classification with Deep Convolutional Neural Networks" (2012) - https://papers.nips.cc/paper/4824-imagenet-classification-wi... (University of Toronto) 6. "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding" (2018) - https://arxiv.org/abs/1810.04805 (Google) 7. "RoBERTa: A Robustly Optimized BERT Pretraining Approach" (2019) - https://arxiv.org/abs/1907.11692 (Facebook AI) 8. "ELMo: Deep contextualized word representations" (2018) - https://arxiv.org/abs/1802.05365 (Allen Institute for Artificial Intelligence) 9. "Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context" (2019) - https://arxiv.org/abs/1901.02860 (Google AI Language) 10. "XLNet: Generalized Autoregressive Pretraining for Language Understanding" (2019) - https://arxiv.org/abs/1906.08237 (Google AI Language) 11. T5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer" (2020) - https://arxiv.org/abs/1910.10683 (Google Research) 12. "Language Models are Few-Shot Learners" (2021) - https://arxiv.org/abs/2005.14165 (OpenAI)

user:	vikashrungta
created:	March 20, 2019
karma:	2