Innervu Knowledge Navigator

Large Language Models as Optimizers

By Chengrun Yang et al
Published on April 15, 2024

Hypergraph Neural Networks

By Y. Feng et al.
Published on None

Truly Sparse Neural Networks at Scale

By Selima Curci et al
Published on None

Exploring Alternatives to Softmax Function

By Kunal Banerjee et al
Published on Nov. 23, 2020

Dynamic Embedding Size Search With Minimum Regret for Streaming Recommender System

By Bowei He et al
Published on None

Vision Transformer With Deformable Attention

By Zhuofan Xia et al
Published on May 24, 2022

Audio Spectrogram Transformer

By Y. Gong et al
Published on None

Rethinking Attention with Performers

By K. Choromanski et al
Published on June 10, 2021

Simplifying Transformer Blocks

By Bobby He et al.
Published on Nov. 3, 2023

Generative Pretraining in Multimodality

By Quan Sun et al
Published on July 11, 2023

Sparse Is Enough In Scaling Transformers

By S. Jaszczur et al
Published on None

Large Language Models as Generalizable Policies for Embodied Tasks

By Andrew Szot et al.
Published on April 16, 2024

Transformer In Transformer

By Kai Han et al
Published on Oct. 26, 2021

Differentiable Architecture Search

By Hanxiao Liu et al
Published on April 23, 2019

Memory Augmented Large Language Models Are Computationally Universal

By Dale Schuurmans et al
Published on Jan. 10, 2023

Scaling Vision Transformers

By X. Zhai et al
Published on June 20, 2022

Point Transformer

By H. Zhao et al
Published on None

DeText: A Deep Text Ranking Framework with BERT

By Weiwei Guo et al
Published on None

Interferometric Imaging of Amplitude and Phase of Spatial Biphoton States

By Danilo Zia et al
Published on None

Diffusion Explainer

By Seongmin Lee et al
Published on None

The Hidden Language of Diffusion Models

By H. Chefer et al
Published on None

Neural Networks and Continuous Time

By Frieder Stolzenburg et al
Published on June 14, 2016

Flashattention

By Tri Daoy et al
Published on June 24, 2022

A Survey on Efficient Training of Transformers

By Bohan Zhuang et al
Published on May 4, 2023

The Boundary of Neural Network Trainability is Fractal

By Jascha Sohl-Dickstein et al
Published on None

Ql Ora: Efficient Finetuning of Quantized Llms

By Tim Dettmers et al
Published on May 23, 2023

OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

By Peng Wang et al
Published on June 1, 2022

The Dawn of Quantum Natural Language Processing

By Riccardo DiSipio et al
Published on None

Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

By Mohammad Shoeybi et al
Published on March 13, 2020

Working Paper Gpts Are Gpts: An Early Look at the Labor Market Impact Potential of Large Language Models

By Tyna Eloundou et al
Published on Aug. 22, 2023

Bolt: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware

By Nicholas Meisburger et al
Published on Oct. 21, 2023

Closed-Form Continuous-Time Neural Networks

By Ramin Hasani et al
Published on March 2, 2022

Small-Scale Proxies for Large-Scale Transformer Training Instabilities

By Mitchell W. Peter et al.
Published on Oct. 16, 2023

Roformer: Enhanced Transformer with Rotary Position Embedding

By J. Su et al.
Published on Nov. 9, 2023

Meta-Transformer: A Unified Framework for Multimodal Learning

By Y. Zhang et al
Published on July 20, 2023

Mcunet: Tiny Deep Learning on IoT Devices

By Ji Lin et al
Published on Nov. 19, 2020

PaLM: Scaling Language Modeling with Pathways

By Aakanksha Chowdhery et al
Published on Oct. 5, 2022

Fast Inference from Transformers via Speculative Decoding

By Y. Leviathan et al
Published on June 10, 2023

Masked Discrimination for Self-Supervised Learning on Point Clouds

By Haotian Liu et al
Published on Aug. 1, 2022

Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizers

By Damai Dai et al
Published on None

Retentive Network: A Successor to Transformer for Large Language Models

By Y. Sun et al
Published on Aug. 9, 2023

Transcending Scaling Laws with 0.1% Extra Compute

By Yi Tay et al.
Published on Nov. 16, 2022

Ibot : Image Bert Pre-Training with Online Tokenizer

By J. Zhou et al.
Published on June 10, 2022

GPT4roi: Instruction Tuning Large Language Model on Region-of-Interest

By Shilong Zhang et al
Published on Oct. 13, 2023

DeepSpeed Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale

By Reza Yazdani et al
Published on None

Flexiast: Flexibility Is What AST Needs

By J. Feng et al
Published on None

Sailor: Structural Augmentation Based Tail Node Representation Learning

By J. Liao et al
Published on Jan. 1, 2023

Gpt-4 Technical Report

By Openai et al
Published on March 4, 2024

Deep Polynomial Neural Networks

By G. G. Chrysos et al
Published on Feb. 27, 2021

Learning With Capsules: A Survey

By Fabio De Sousa Ribeiro et al
Published on None

Text-To-Image Diffusion Models in Generative AI: A Survey

By C. Zhang et al
Published on Aug. 10, 2015

Lambda Networks: Modeling Long-Range Interactions Without Attention

By Irwan Bello et al
Published on Feb. 17, 2021

Reformer: The Efficient Transformer

By Nikita Kitaev et al
Published on Feb. 18, 2020

Multimodal Contrastive Learning with LIMoE: The Language-Image Mixture of Experts

By Basil Mustafa et al
Published on June 6, 2022

Squeeze-and-Excitation Networks

By J. Hu et al
Published on None

Attention Calibration for Transformer-based Sequential Recommendation

By Peilin Zhou et al
Published on Oct. 21, 2023

Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles

By Chaitanya Ryali et al
Published on June 1, 2023

Vision Transformer: Vit and its Derivatives

By Zujun Fu et al
Published on May 25, 2022

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

By William Fedus et al.
Published on April 22, 2024

Visual Instruction Tuning

By Haotian Liu et al
Published on None

Neural Ordinary Differential Equations

By Ricky T. Q. Chen et al
Published on None

Graph Attention Networks

By Petar Veličković et al
Published on June 10, 2018

Feedback Networks

By Amir R. Zamir et al
Published on Aug. 20, 2017

Image as a Foreign Language: BE IT Pretraining for All Vision and Vision-Language Tasks

By Wenhui Wang et al
Published on Aug. 31, 2022

Collaborative Teacher-Student Learning via Multiple Knowledge Transfer

By Liyuan Sun et al
Published on Jan. 27, 2021

Decision Transformer: Reinforcement Learning via Sequence Modeling

By Lili Chen et al
Published on June 24, 2021

Vlm O: Unified Vision-Language Pre-Training With Mixture-Of-Modality-Experts

By Hangbo Bao et al
Published on May 27, 2022

Beyond The Imitation Game: Quantifying And Extrapolating The Capabilities Of Language Models

By Aarohi Srivastava et al
Published on June 12, 2023

The Dawn of Lmms: Preliminary Explorations with GPT-4V(ision)

By Zhengyuan Yang et al
Published on None

Gpt-4 Technical Report Openai

By Openai
Published on March 27, 2023

Swin Transformer: Hierarchical Vision Transformer Using Shifted Windows

By Ze Liu et al
Published on Aug. 17, 2021

Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks for Node Classification

By Arpit Merchant et al
Published on Oct. 21, 2023

A Survey of Large Language Models

By Wayne Xin Zhao et al
Published on None

Global Self-Attention Networks for Image Recognition

By Shen Zhuoran et al
Published on Oct. 14, 2020

Fractal Net: Ultra-Deep Neural Networks Without Residuals

By Gustav Larsson et al
Published on May 26, 2017

Do Vision Transformers See Like Convolutional Neural Networks?

By Maithra Raghu et al
Published on None

Datacomp: In Search of the Next Generation of Multimodal Datasets

By Samir Yitzhak Gadre et al
Published on Oct. 20, 2023

Hugging GPT: Solving AI Tasks with Chat GPT and its Friends in Hugging Face

By Y. Shen et al
Published on Dec. 3, 2023

Animage is Worth 16x16 Words: Transformers for Image Recognition at Scale

By Alexey Dosovitskiy et al
Published on June 10, 2021

Foundations & Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions

By Paul Pu Liang et al
Published on Oct. 10, 2022

Multimodal Learning with Transformers: A Survey

By Peng Xu et al
Published on May 10, 2023

Neural Architecture Search: Insights From 1000 Papers

By Colin White et al
Published on Jan. 25, 2023

Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models

By Zhiqiu Lin et al
Published on Aug. 3, 2023

Once-For-All: Train One Network and Specialize It for Efficient Deployment

By Han Cai et al
Published on June 10, 2020

G-STO: Sequential Main Shopping Intention Detection via Graph-Regularized Stochastic Transformer

By Y. Zhuang et al
Published on None

Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training

By Ziwei Fan et al
Published on None

Patch N’ Pack: NaViT, a Vision Transformer for Any Aspect Ratio and Resolution

By Mostafa Dehghani et al
Published on None

Few-shot Text-to-Image Generation

By Y. Zhou et al
Published on None

AdaMCT: Adaptive Mixture of CNN-Transformer for Sequential Recommendation

By Juyong Jiang et al
Published on None

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

By M. Tan et al.
Published on June 10, 2019

Extending Context Window of Large Language Models via Position Interpolation

By Shouyuan Chen et al.
Published on None

Lora: Low-Rank Adaptation of Large Language Models

By Edward Hu et al
Published on Oct. 16, 2021

Longnet: Scaling Transformers to 1,000,000,000 Tokens

By J. Ding et al
Published on July 19, 2023

Swin Transformer V2: Scaling Up Capacity and Resolution

By Ze Liu et al
Published on None

Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting

By B. Lima et al
Published on Sept. 29, 2020

Sdxl: Improving Latent Diffusion Models for High-Resolution Image Synthesis

By Dustin Podell et al
Published on July 4, 2023

The Troubling Emergence of Hallucination in Large Language Models – An Extensive Definition, Quantification, and Prescriptive Remediations

By Vipula Rawte et al
Published on Oct. 23, 2023

Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding

By S. Luo et al
Published on Nov. 3, 2021

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture

By Mahmoud Assran et al
Published on None

On the Expressivity Role of Layernorm in Transformers’ Attention

By Shaked Brodyy et al.
Published on None

Tensor Decomposition for Model Reduction in Neural Networks: A Review

By X. Liu et al.
Published on None

Relational Inductive Biases, Deep Learning, and Graph Networks

By Peter W. Battaglia et al
Published on Oct. 17, 2018

Star-Transformer

By Qipeng Guo et al
Published on None

Scaling Vision Transformers to 22 Billion Parameters

By Mostafa Dehghani et al
Published on None

StarCoder: May the Source Be with You

By Raymond Li et al
Published on Dec. 10, 2023

Large-Scale Multi-Modal Pre-Trained Models: A Comprehensive Survey

By Xiao Wang et al
Published on April 10, 2024