ImageBind: One Embedding Space To Bind Them All
ImageBind is a multimodality model by Meta AI. In this post, we dive into ImageBind research paper to understand what it is and how it works.
Consistency Models – Optimizing Diffusion Models Inference
Consistency models are a new type of generative models which were introduced by Open AI, and in this post we will dive into how they work
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LIMA from Meta AI – Less Is More for Alignment of LLMs
In this post we explain LIMA, a LLM by Meta AI which was fine-tuned on only 1000 samples, yet it achieves competitive results with top LLMs
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Shepherd: A Critic for Language Model Generation
Dive into Shepherd, a LLM from Meta AI which is purposed to critique responses from other LLMs, a step in resolving LLMs hallucinations.
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Universal and Transferable Adversarial LLM Attacks
LLMs are aligned for safety to avoid generation of harmful content. In this post we review a paper that is able to successfully attack LLMs.
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Meta-Transformer: A Unified Framework for Multimodal Learning
In this post we dive into Meta-Transformer, a unified framework for multimodal learning, which can process information from 12(!) modalities
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From Sparse to Soft Mixture of Experts
In this post we review Google DeepMind’s paper that introduces Soft Mixture of Experts, a fully-differentiable sparse Transformer.
What is YOLO-NAS and How it Was Created
YOLO-NAS is an object detection model with the best accuracy-latency tradeoff to date. In this post we explain how it was created.