Trending Research
Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Models
In RDMs, a set of nearest neighbors is retrieved from an external database during training for each training instance, and the diffusion model is conditioned on these informative samples.
Elucidating the Design Space of Diffusion-Based Generative Models
We argue that the theory and practice of diffusion-based generative models are currently unnecessarily convoluted and seek to remedy the situation by presenting a design space that clearly separates the concrete design choices.
Deepchecks: A Library for Testing and Validating Machine Learning Models and Data
This paper presents Deepchecks, a Python library for comprehensively validating machine learning models and data.
Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentation
cardwing/codes-for-pvkd
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CVPR 2022
This article addresses the problem of distilling knowledge from a large teacher model to a slim student network for LiDAR semantic segmentation.
Ranked #14 on
LIDAR Semantic Segmentation
on nuScenes
FRA-RIR: Fast Random Approximation of the Image-source Method
yluo42/fra-rir
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The training of modern speech processing systems often requires a large amount of simulated room impulse response (RIR) data in order to allow the systems to generalize well in real-world, reverberant environments.
GPT-NeoX-20B: An Open-Source Autoregressive Language Model
labmlai/annotated_deep_learning_paper_implementations
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BigScience (ACL) 2022
We introduce GPT-NeoX-20B, a 20 billion parameter autoregressive language model trained on the Pile, whose weights will be made freely and openly available to the public through a permissive license.
Ranked #7 on
Multi-task Language Understanding
on MMLU
Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN
We observe that MIM essentially teaches the model to learn better middle-level interactions among patches and extract more generalized features.
ferret: a Framework for Benchmarking Explainers on Transformers
g8a9/ferret
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Many interpretability tools allow practitioners and researchers to explain Natural Language Processing systems.
Patching open-vocabulary models by interpolating weights
We study model patching, where the goal is to improve accuracy on specific tasks without degrading accuracy on tasks where performance is already adequate.
towhee
towhee-io/towhee
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ICCV 2019
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
