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09/04/2023
Safe and Robust Watermark Injection with a Single OoD Image
Training a high-performance deep neural network requires large amounts o...
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08/22/2023
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts
Cross-scene generalizable NeRF models, which can directly synthesize nov...
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08/19/2023
Robust Mixture-of-Expert Training for Convolutional Neural Networks
Sparsely-gated Mixture of Expert (MoE), an emerging deep model architect...
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08/17/2023
How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers?
Pruning has emerged as a powerful technique for compressing deep neural ...
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08/11/2023
INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation Processing
An increasing number of researchers are finding use for nth-order gradie...
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08/01/2023
Doubly Robust Instance-Reweighted Adversarial Training
Assigning importance weights to adversarial data has achieved great succ...
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07/20/2023
Physics-Driven Turbulence Image Restoration with Stochastic Refinement
Image distortion by atmospheric turbulence is a stochastic degradation, ...
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07/20/2023
Reference-based Painterly Inpainting via Diffusion: Crossing the Wild Reference Domain Gap
Have you ever imagined how it would look if we placed new objects into p...
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07/05/2023
Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities
Recently, zero-shot (or training-free) Neural Architecture Search (NAS) ...
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06/29/2023
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude
Whole-body biometric recognition is an important area of research due to...
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06/24/2023
H_2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models
Large Language Models (LLMs), despite their recent impressive accomplish...
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06/18/2023
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication
Graphs are omnipresent and GNNs are a powerful family of neural networks...
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06/18/2023
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models
Large pre-trained transformers have been receiving explosive attention i...
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06/13/2023
Learning to Estimate 6DoF Pose from Limited Data: A Few-Shot, Generalizable Approach using RGB Images
The accurate estimation of six degrees-of-freedom (6DoF) object poses is...
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06/06/2023
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter
Large pre-trained transformers are show-stealer in modern-day deep learn...
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05/30/2023
Dynamic Sparsity Is Channel-Level Sparsity Learner
Sparse training has received an upsurging interest in machine learning d...
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05/30/2023
Are Large Kernels Better Teachers than Transformers for ConvNets?
This paper reveals a new appeal of the recently emerged large-kernel Con...
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05/30/2023
Edge-MoE: Memory-Efficient Multi-Task Vision Transformer Architecture with Task-level Sparsity via Mixture-of-Experts
Computer vision researchers are embracing two promising paradigms: Visio...
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05/29/2023
Towards Constituting Mathematical Structures for Learning to Optimize
Learning to Optimize (L2O), a technique that utilizes machine learning t...
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05/25/2023
Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models
Text-to-image (T2I) research has grown explosively in the past year, owi...
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05/25/2023
POPE: 6-DoF Promptable Pose Estimation of Any Object, in Any Scene, with One Reference
Despite the significant progress in six degrees-of-freedom (6DoF) object...
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05/12/2023
MMG-Ego4D: Multi-Modal Generalization in Egocentric Action Recognition
In this paper, we study a novel problem in egocentric action recognition...
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05/01/2023
In-Context Learning Unlocked for Diffusion Models
We present Prompt Diffusion, a framework for enabling in-context learnin...
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04/28/2023
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation
For a complicated algorithm, its implementation by a human programmer us...
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04/25/2023
Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
Diffusion models are powerful, but they require a lot of time and data t...
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04/12/2023
AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection
The short-form videos have explosive popularity and have dominated the n...
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04/06/2023
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling
Graph neural networks (GNNs) have been widely applied to learning over g...
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03/30/2023
Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models
The unlearning problem of deep learning models, once primarily an academ...
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03/30/2023
PAIR-Diffusion: Object-Level Image Editing with Structure-and-Appearance Paired Diffusion Models
Image editing using diffusion models has witnessed extremely fast-paced ...
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03/23/2023
Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators
Recent text-to-video generation approaches rely on computationally heavy...
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03/03/2023
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!
Sparse Neural Networks (SNNs) have received voluminous attention predomi...
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03/02/2023
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers
Despite their remarkable achievement, gigantic transformers encounter si...
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03/02/2023
Learning to Grow Pretrained Models for Efficient Transformer Training
Scaling transformers has led to significant breakthroughs in many domain...
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02/28/2023
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation
Learning to Optimize (L2O) has drawn increasing attention as it often re...
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02/27/2023
You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction
Link prediction is central to many real-world applications, but its perf...
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02/27/2023
Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations
Recently, both Contrastive Learning (CL) and Mask Image Modeling (MIM) d...
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02/24/2023
Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights?
Given a robust model trained to be resilient to one or multiple types of...
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02/22/2023
Learning to Generalize Provably in Learning to Optimize
Learning to optimize (L2O) has gained increasing popularity, which autom...
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02/06/2023
Ten Lessons We Have Learned in the New "Sparseland": A Short Handbook for Sparse Neural Network Researchers
This article does not propose any novel algorithm or new hardware for sp...
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01/26/2023
Evaluate underdiagnosis and overdiagnosis bias of deep learning model on primary open-angle glaucoma diagnosis in under-served patient populations
In the United States, primary open-angle glaucoma (POAG) is the leading ...
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01/01/2023
Theoretical Characterization of How Neural Network Pruning Affects its Generalization
It has been observed in practice that applying pruning-at-initialization...
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01/01/2023
Sharper analysis of sparsely activated wide neural networks with trainable biases
This work studies training one-hidden-layer overparameterized ReLU netwo...
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12/30/2022
Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression Search
Learning efficient and interpretable policies has been a challenging tas...
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12/06/2022
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances
Deep neural networks (DNNs) have rapidly become a de facto choice for me...
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12/03/2022
StegaNeRF: Embedding Invisible Information within Neural Radiance Fields
Recent advances in neural rendering imply a future of widespread visual ...
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11/29/2022
NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360° Views
Virtual reality and augmented reality (XR) bring increasing demand for 3...
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11/28/2022
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets
Recent works have impressively demonstrated that there exists a subnetwo...
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11/23/2022
Search Behavior Prediction: A Hypergraph Perspective
Although the bipartite shopping graphs are straightforward to model sear...
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11/17/2022
AligNeRF: High-Fidelity Neural Radiance Fields via Alignment-Aware Training
Neural Radiance Fields (NeRFs) are a powerful representation for modelin...
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11/15/2022