AI Papers Academy, Author at AI Papers Academy

CLLMs: Consistency Large Language Models

In this post we dive into Consistency Large Language Models (CLLMs), a new family of models which can dramatically speedup LLMs inference!

Learn about Representation Finetuning (ReFT) by Stanford University, a method to fine-tune large language models (LLMs) efficiently.

What if we could discover OpenAI models internal weights? In this post we dive into a paper which presents an attack that steals LLMs data.

Explore V-JEPA, which stands for Video Joint-Embedding Predicting Architecture. Another step in Meta AI’s journey for human-like AI

In this post we dive into the era of 1-bit LLMs paper by Microsoft, which shows a promising direction for low cost large language models

In this post we dive into the Self-Rewarding Language Models paper by Meta AI, which can possibly be a step towards open-source AGI

Diving into a research paper introducing an innovative method to enhance LLM inference efficiency using memory offloading

In this post we dive into TinyGPT-V, a small but mighty Multimodal LLM which brings Phi-2 success to vision-language tasks

In this post we dive into LLM in a flash paper by Apple, that introduces a method to run LLMs on devices that have limited memory

In this post we go back to the important vision transformers paper, to understand how ViT adapted transformers to computer vision