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@@ -46,7 +46,7 @@ At DAIR.AI we ❤️ reading ML papers so we've created this repo to highlight t
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| 2) **Claude 2** - presents a detailed model card for Claude 2 along with results on a range of safety, alignment, and capabilities evaluations. | [Paper](https://www-files.anthropic.com/production/images/Model-Card-Claude-2.pdf), [Tweet](https://twitter.com/AnthropicAI/status/1678759122194530304?s=20) |
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| 3) **Secrets of RLHF in LLMs** - takes a closer look at RLHF and explores the inner workings of PPO with code included. | [Paper](https://arxiv.org/abs/2307.04964), [Tweet](https://twitter.com/omarsar0/status/1678938028918571009?s=20) |
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| 4) **LongLLaMA** - employs a contrastive training process to enhance the structure of the (key, value) space to extend context length; presents a fine-tuned model that lengthens context and demonstrates improvements in long context tasks. | [Paper](https://arxiv.org/abs/2307.03170v1), [Tweet](https://twitter.com/s_tworkowski/status/1677125863429795840?s=20) |
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-| 5. **Patch n’ Pack: NaViT** - introduces a vision transformer for any aspect ratio and resolution through sequence packing; enables flexible model usage, improved training efficiency, and transfers to tasks involving image and video classification among others. | [Paper](https://arxiv.org/abs/2307.06304), [Tweet](https://twitter.com/m__dehghani/status/1679558751248850969?s=20)
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+| 5) **Patch n’ Pack: NaViT** - introduces a vision transformer for any aspect ratio and resolution through sequence packing; enables flexible model usage, improved training efficiency, and transfers to tasks involving image and video classification among others. | [Paper](https://arxiv.org/abs/2307.06304), [Tweet](https://twitter.com/m__dehghani/status/1679558751248850969?s=20)
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| 6) **LLMs as General Pattern Machines** - shows that even without any additional training, LLMs can serve as general sequence modelers, driven by in-context learning; this work applies zero-shot capabilities to robotics and shows that it’s possible to transfer the pattern among words to actions. | [Paper](https://arxiv.org/abs/2307.04721), [Tweet](https://twitter.com/DrJimFan/status/1679898692307005440?s=20) |
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| 7) **HyperDreamBooth** - introduces a smaller, faster, and more efficient version of Dreambooth; enables personalization of text-to-image diffusion model using a single input image, 25x faster than Dreambooth. | [Paper](https://arxiv.org/abs/2307.06949), [Tweet](https://twitter.com/natanielruizg/status/1679893292618752000?s=20) |
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| 8) **Teaching Arithmetics to Small Transformers** - trains small transformer models on chain-of-thought style data to significantly improve accuracy and convergence speed; it highlights the importance of high-quality instructive data for rapidly eliciting arithmetic capabilities. | [Paper](https://arxiv.org/abs/2307.03381), [Tweet](https://twitter.com/DimitrisPapail/status/1678407512637284352?s=20) |
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Elvis Saravia