"computational efficiency" Papers
197 papers found • Page 4 of 4
Conference
FRDiff : Feature Reuse for Universal Training-free Acceleration of Diffusion Models
Junhyuk So, Jungwon Lee, Eunhyeok Park
Frugal 3D Point Cloud Model Training via Progressive Near Point Filtering and Fused Aggregation
Donghyun Lee, Yejin Lee, Jae W. Lee et al.
Grid-Attention: Enhancing Computational Efficiency of Large Vision Models without Fine-Tuning
Pengyu Li, Biao Wang, Tianchu Guo et al.
Grid Diffusion Models for Text-to-Video Generation
Taegyeong Lee, Soyeong Kwon, Taehwan Kim
Headless Language Models: Learning without Predicting with Contrastive Weight Tying
Nathan Godey, Éric Clergerie, Benoît Sagot
Hierarchical Separable Video Transformer for Snapshot Compressive Imaging
Ping Wang, Yulun Zhang, Lishun Wang et al.
HPE-Li: WiFi-enabled Lightweight Dual Selective Kernel Convolution for Human Pose Estimation
Gian Toan D., Tien Dac Lai, Thien Van Luong et al.
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering
Sheng Liu, Haotian Ye, Lei Xing et al.
Inducing Point Operator Transformer: A Flexible and Scalable Architecture for Solving PDEs
Seungjun Lee, TaeIL Oh
Learning Causal Dynamics Models in Object-Oriented Environments
Zhongwei Yu, Jingqing Ruan, Dengpeng Xing
Learning Temporal Resolution in Spectrogram for Audio Classification
Haohe Liu, Xubo Liu, Qiuqiang Kong et al.
LION: Implicit Vision Prompt Tuning
Haixin Wang, Jianlong Chang, Yihang Zhai et al.
LiteSAM is Actually what you Need for segment Everything
Jianhai Fu, Yuanjie Yu, Ningchuan Li et al.
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models
Gianni Franchi, Olivier Laurent, Maxence Leguéry et al.
Mixture of Efficient Diffusion Experts Through Automatic Interval and Sub-Network Selection
Alireza Ganjdanesh, Yan Kang, Yuchen Liu et al.
Object-Centric Diffusion for Efficient Video Editing
Kumara Kahatapitiya, Adil Karjauv, Davide Abati et al.
ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
Dongha Kim, Jaesung Hwang, Jongjin Lee et al.
One-stage Prompt-based Continual Learning
Youngeun Kim, YUHANG LI, Priyadarshini Panda
Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation
Yixiao Wang, Chen Tang, Lingfeng Sun et al.
Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty
Kaizhao Liu, Jose Blanchet, Lexing Ying et al.
Partially Stochastic Infinitely Deep Bayesian Neural Networks
Sergio Calvo Ordoñez, Matthieu Meunier, Francesco Piatti et al.
PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design
Alexandre Duval, Victor Schmidt, Santiago Miret et al.
Quantization-Friendly Winograd Transformations for Convolutional Neural Networks
Vladimir Protsenko, Vladimir Kryzhanovskiy, Alexander Filippov
Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
Sudeep Salgia, Sattar Vakili, Qing Zhao
RegionDrag: Fast Region-Based Image Editing with Diffusion Models
Jingyi Lu, Xinghui Li, Kai Han
Removing Rows and Columns of Tokens in Vision Transformer enables Faster Dense Prediction without Retraining
Diwei Su, cheng fei, Jianxu Luo
Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution
Guangyuan Li, Chen Rao, Juncheng Mo et al.
Rethinking Video Deblurring with Wavelet-Aware Dynamic Transformer and Diffusion Model
chen rao, Guangyuan Li, Zehua Lan et al.
SAFNet: Selective Alignment Fusion Network for Efficient HDR Imaging
Lingtong Kong, Bo Li, Yike Xiong et al.
Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement
Xiuquan Hou, Meiqin Liu, Senlin Zhang et al.
Saliency strikes back: How filtering out high frequencies improves white-box explanations
Sabine Muzellec, Thomas FEL, Victor Boutin et al.
Scaling Laws for Fine-Grained Mixture of Experts
Jan Ludziejewski, Jakub Krajewski, Kamil Adamczewski et al.
ScanFormer: Referring Expression Comprehension by Iteratively Scanning
Wei Su, Peihan Miao, Huanzhang Dou et al.
See More Details: Efficient Image Super-Resolution by Experts Mining
Eduard Zamfir, Zongwei Wu, Nancy Mehta et al.
Self-Adapting Large Visual-Language Models to Edge Devices across Visual Modalities
Kaiwen Cai, ZheKai Duan, Gaowen Liu et al.
SeTformer Is What You Need for Vision and Language
Pourya Shamsolmoali, Masoumeh Zareapoor, Eric Granger et al.
SMFANet: A Lightweight Self-Modulation Feature Aggregation Network for Efficient Image Super-Resolution
mingjun zheng, Long Sun, Jiangxin Dong et al.
SNP: Structured Neuron-level Pruning to Preserve Attention Scores
Kyunghwan Shim, Jaewoong Yun, Shinkook Choi
Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting
Anthony Chen, Huanrui Yang, Yulu Gan et al.
Stripe Observation Guided Inference Cost-free Attention Mechanism
Zhongzhan Huang, Shanshan Zhong, Wushao Wen et al.
Thermometer: Towards Universal Calibration for Large Language Models
Maohao Shen, Subhro Das, Kristjan Greenewald et al.
Transformer-Based Selective Super-resolution for Efficient Image Refinement
Tianyi Zhang, Kishore Kasichainula, Yaoxin Zhuo et al.
Translating Subgraphs to Nodes Makes Simple GNNs Strong and Efficient for Subgraph Representation Learning
Dongkwan Kim, Alice Oh
Turbo: Informativity-Driven Acceleration Plug-In for Vision-Language Large Models
Chen Ju, Haicheng Wang, Haozhe Cheng et al.
Understanding and Improving Optimization in Predictive Coding Networks
Nicholas Alonso, Jeffrey Krichmar, Emre Neftci
Various Lengths, Constant Speed: Efficient Language Modeling with Lightning Attention
Zhen Qin, Weigao Sun, Dong Li et al.
Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention
Xingyu Zhou, Leheng Zhang, Xiaorui Zhao et al.