##############################################################################
Multimodal
##############################################################################
******************************************************************************************
Diffusion
******************************************************************************************
.. important::
	* [calvinyluo.com] `Understanding Diffusion Models: A Unified Perspective <https://www.calvinyluo.com/2022/08/26/diffusion-tutorial.html>`_
	* [arxiv] `Tutorial on Diffusion Models for Imaging and Vision <https://arxiv.org/abs/2403.18103>`_
	* `Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning <https://arxiv.org/abs/2407.20798>`_

******************************************************************************************
Tech
******************************************************************************************
* [anthropic.com] 

	* `Anthropic Research <https://www.anthropic.com/research>`_
	* `Towards Monosemanticity: Decomposing Language Models With Dictionary Learning <https://transformer-circuits.pub/2023/monosemantic-features>`_
	* `Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet <https://transformer-circuits.pub/2024/scaling-monosemanticity/index.html>`_
	* `Towards Understanding Sycophancy in Language Models <https://arxiv.org/abs/2310.13548>`_
	* `Specific versus General Principles for Constitutional AI <https://arxiv.org/abs/2310.13798>`_
	* `Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training <https://arxiv.org/abs/2401.05566>`_
	* `Simple probes can catch sleeper agents <https://www.anthropic.com/research/probes-catch-sleeper-agents>`_
	* `Challenges in evaluating AI systems <https://www.anthropic.com/research/evaluating-ai-systems>`_
	* `AI Governance and Accountability: An Analysis of Anthropic's Claude <https://arxiv.org/pdf/2407.01557v1>`_
	* `Claude <https://www.anthropic.com/news/claude-3-family>`_ (`Claude on Bedrock <https://aws.amazon.com/bedrock/claude/>`_)
* [mistral.ai] `Mixtral <https://mistral.ai/news/mixtral-of-experts/>`_ (`Mixtral on Bedrock <https://aws.amazon.com/bedrock/mistral/>`_)
* [ai.meta.com `Llama <https://ai.meta.com/blog/meta-llama-3/>`_ (`Llama on Bedrock <https://aws.amazon.com/bedrock/llama/>`_)
* [stability.ai] `Stable Diffusion <https://stability.ai/news/stable-diffusion-3-research-paper>`_ (`Stable Diffusion on Bedrock <https://aws.amazon.com/bedrock/stable-diffusion/>`_)
* [blog.google] `Gemini <https://blog.google/technology/ai/google-gemini-ai/>`_
* [openai.com]

	* `GPT-4o <https://openai.com/index/hello-gpt-4o/>`_
	* [DALL·E]: `Creating images from text <https://openai.com/index/dall-e/>`_
	* [SoRa]: `Video generation models as world simulators <https://openai.com/index/video-generation-models-as-world-simulators/>`_
	* `DALL·E 2 <https://openai.com/index/dall-e-2/>`_

******************************************************************************************
Resources
******************************************************************************************
Industry
==========================================================================================
* Amazon Science: `ML <https://aws.amazon.com/ai/machine-learning/>`_, `GenAI <https://aws.amazon.com/ai/generative-ai/>`_

	* `A quick guide to Amazon’s papers at ICML 2024 <https://www.amazon.science/blog/a-quick-guide-to-amazons-papers-at-icml-2024>`_
	* `List of publications <https://www.amazon.science/publications>`_
	* `Conversational AI <https://www.amazon.science/research-areas/conversational-ai-natural-language-processing>`_
	* `Large language models (LLMs) <https://www.amazon.science/tag/large-language-models>`_
	* `Computer vision <https://www.amazon.science/research-areas/computer-vision>`_
	* `Code and datasets <https://www.amazon.science/code-and-datasets>`_
	* `AWS News Blog <https://aws.amazon.com/blogs/aws/>`_:

		* `Category: Amazon Machine Learning <https://aws.amazon.com/blogs/aws/category/artificial-intelligence/amazon-machine-learning/>`_
		* `Category: Generative AI <https://aws.amazon.com/blogs/aws/category/artificial-intelligence/generative-ai/>`_
* Pinterest

	* `PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest <https://dl.acm.org/doi/pdf/10.1145/3394486.3403280>`_
* [research.google] `Transformers in music recommendation <https://research.google/blog/transformers-in-music-recommendation/>`_

Misc
==========================================================================================
* Yann LeCun

	* `Google Scholar Page <https://scholar.google.com/citations?hl=en&user=WLN3QrAAAAAJ&view_op=list_works&sortby=pubdate>`_
	* `Arxiv Page <https://arxiv.org/find/all/1/all:+AND+yann+lecun/0/1/0/all/0/1>`_
	
* [neptune.ai] `6 GAN Architectures You Really Should Know  <https://neptune.ai/blog/6-gan-architectures>`_

Paper List
==========================================================================================
.. csv-table:: 
	:header: "Year","Paper"
	:align: center

		2023,Align your latents: High-resolution video synthesis with latent diffusion models
		2023,Photorealistic video generation with diffusion models
		2023,Patch n'Pack: NaViT a Vision Transformer for any Aspect Ratio and Resolution
		2023,Scalable diffusion models with transformers
		2023,Improving image generation with better captions
		2022,Generating long videos of dynamic scenes
		2022,NUwa: Visual synthesis pre-training for neural visual world creation
		2022,Imagen video: High definition video generation with diffusion models
		2022,Masked autoencoders are scalable vision learners
		2022,High-resolution image synthesis with latent diffusion models
		2022,Elucidating the design space of diffusion-based generative models
		2022,Scaling autoregressive models for content-rich text-to-image generation
		2022,Hierarchical text-conditional image generation with clip latents
		2021,Videogpt: Video generation using vq-vae and transformers
		2021,Vivit: A video vision transformer
		2021,Improved denoising diffusion probabilistic models
		2021,Diffusion Models Beat GANs on Image Synthesis
		2021,Zero-shot text-to-image generation
		2021,Sdedit: Guided image synthesis and editing with stochastic differential equations
		2020,Language models are few-shot learners
		2020,An image is worth 16x16 words: Transformers for image recognition at scale
		2020,Denoising diffusion probabilistic models
		2020,Generative pretraining from pixels
		2019,Adversarial video generation on complex datasets
		2018,World models
		2018,Mocogan: Decomposing motion and content for video generation
		2017,Recurrent environment simulators
		2017,Attention is all you need
		2016,Generating videos with scene dynamics
		2015,Unsupervised learning of video representations using lstms
		2015,Deep unsupervised learning using nonequilibrium thermodynamics
		2013,Auto-encoding variational bayes