Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Visual AutoRegressive Modeling:Scalable Image Generation via Next-Scale Prediction

Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention

Learning to (Learn at Test Time): RNNs with Expressive Hidden States

MLBBQ: “Are Transformers Effective for Time Series Forecasting?” by Joanne Wardell

Stable Diffusion 3: Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits and BitNet

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

CoPE - Contextual Position Encoding: Learning to Count What's Important

Attention in transformers, visually explained | Chapter 6, Deep Learning

Bruno Mars Playlist 2024 - Best Songs Collection Full Album - The Best Of Bruno Mars - Greatest Hits

Think Fast, Talk Smart: Communication Techniques

Attending to Topological Spaces: The Cellular Transformer

Round and Round We Go! What makes Rotary Positional Encodings useful?

Lagu Terbaik DEWA 19 Indonesia Terbaik & Terpopuler Tahun 2000an

How I animate 3Blue1Brown | A Manim demo with Ben Sparks

NEW: INFINI Attention w/ 1 Mio Context Length

Stanford CS25: V2 I Introduction to Transformers w/ Andrej Karpathy

TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters

Reflections on Models of Language: What's the Next Thing To Do? (Part 2 of 2)