2024 Poster Papers

8,865 papers found • Page 35 of 178

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression

Junyuan Hong, Jinhao Duan, Chenhui Zhang et al.

ICML 2024posterarXiv:2403.15447

DECOLLAGE: 3D Detailization by Controllable, Localized, and Learned Geometry Enhancement

Qimin Chen, Zhiqin Chen, Vladimir Kim et al.

ECCV 2024posterarXiv:2409.06129
6
citations

DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization

Xiangxin Zhou, Xiwei Cheng, Yuwei Yang et al.

ICLR 2024posterarXiv:2403.13829

Decomposable Submodular Maximization in Federated Setting

Akbar Rafiey

ICML 2024posterarXiv:2402.00138

Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation

Fahimeh Hosseini Noohdani, Parsa Hosseini, Aryan Yazdan Parast et al.

CVPR 2024posterarXiv:2402.18919
17
citations

Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems

Hyungjin Chung, Suhyeon Lee, Jong Chul YE

ICLR 2024posterarXiv:2303.05754
116
citations

Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics

Noga Mudrik, Yenho Chen, Eva Yezerets et al.

ICML 2024posterarXiv:2206.02972

Decomposed Vector-Quantized Variational Autoencoder for Human Grasp Generation

zhe zhao, Mengshi Qi, Huadong Ma

ECCV 2024posterarXiv:2407.14062
4
citations

Decomposing and Editing Predictions by Modeling Model Computation

Harshay Shah, Andrew Ilyas, Aleksander Madry

ICML 2024posterarXiv:2404.11534

Decomposing Disease Descriptions for Enhanced Pathology Detection: A Multi-Aspect Vision-Language Pre-training Framework

Vu Minh Hieu Phan, Yutong Xie, Yuankai Qi et al.

CVPR 2024posterarXiv:2403.07636

Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Bairu Hou, Yujian Liu, Kaizhi Qian et al.

ICML 2024posterarXiv:2311.08718

Decomposition Betters Tracking Everything Everywhere

Rui Li, Dong Liu

ECCV 2024posterarXiv:2407.06531

Decomposition of Neural Discrete Representations for Large-Scale 3D Mapping

Minseong Park, Suhan Woo, Euntai Kim

ECCV 2024posterarXiv:2407.15554
2
citations

De-confounded Data-free Knowledge Distillation for Handling Distribution Shifts

Yuzheng Wang, Dingkang Yang, Zhaoyu Chen et al.

CVPR 2024posterarXiv:2403.19539
17
citations

De-confounded Gaze Estimation

Ziyang Liang, Yiwei Bao, Feng Lu

ECCV 2024poster
6
citations

DeconfuseTrack: Dealing with Confusion for Multi-Object Tracking

Cheng Huang, Shoudong Han, Mengyu He et al.

CVPR 2024poster

De-Confusing Pseudo-Labels in Source-Free Domain Adaptation

Idit Diamant, Amir Rosenfeld, Idan Achituve et al.

ECCV 2024posterarXiv:2401.01650
4
citations

Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces

Omer Nahum, Gali Noti, David Parkes et al.

ICLR 2024posterarXiv:2306.10606
5
citations

Deconstructing the Goldilocks Zone of Neural Network Initialization

Artem Vysogorets, Anna Dawid, Julia Kempe

ICML 2024posterarXiv:2402.03579

DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection

Zhi Zhou, Ming Yang, Jiang-Xin Shi et al.

ICML 2024posterarXiv:2406.00345

DE-COP: Detecting Copyrighted Content in Language Models Training Data

André Duarte, Xuandong Zhao, Arlindo Oliveira et al.

ICML 2024posterarXiv:2402.09910

DeCoTR: Enhancing Depth Completion with 2D and 3D Attentions

Yunxiao Shi, Manish Singh, Hong Cai et al.

CVPR 2024posterarXiv:2403.12202
8
citations

Decoupled Pseudo-labeling for Semi-Supervised Monocular 3D Object Detection

Jiacheng Zhang, Jiaming Li, Xiangru Lin et al.

CVPR 2024posterarXiv:2403.17387
19
citations

Decouple then Classify: A Dynamic Multi-view Labeling Strategy with Shared and Specific Information

Xinhang Wan, Jiyuan Liu, Xinwang Liu et al.

ICML 2024poster

Decoupling Common and Unique Representations for Multimodal Self-supervised Learning

Yi Wang, Conrad M Albrecht, Nassim Ait Ali Braham et al.

ECCV 2024posterarXiv:2309.05300

Decoupling Feature Extraction and Classification Layers for Calibrated Neural Networks

Mikkel Jordahn, Pablo Olmos

ICML 2024posterarXiv:2405.01196

Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods

Wenzhi Gao, Chunlin Sun, Chenyu Xue et al.

ICML 2024posterarXiv:2402.07108

Decoupling regularization from the action space

Sobhan Mohammadpour, Emma Frejinger, Pierre-Luc Bacon

ICLR 2024posterarXiv:2406.05953

Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation

Shuting He, Henghui Ding

CVPR 2024posterarXiv:2404.03645
64
citations

Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks

Tianyu Fan, Lirong Wu, Yufei Huang et al.

ICLR 2024posterarXiv:2403.01400

De-Diffusion Makes Text a Strong Cross-Modal Interface

Chen Wei, Chenxi Liu, Siyuan Qiao et al.

CVPR 2024posterarXiv:2311.00618
17
citations

DeepCache: Accelerating Diffusion Models for Free

Xinyin Ma, Gongfan Fang, Xinchao Wang

CVPR 2024posterarXiv:2312.00858
265
citations

Deep Companion Learning: Enhancing Generalization Through Historical Consistency

Ruizhao Zhu, Venkatesh Saligrama

ECCV 2024posterarXiv:2407.18821

Deep Confident Steps to New Pockets: Strategies for Docking Generalization

Gabriele Corso, Arthur Deng, Nicholas Polizzi et al.

ICLR 2024posterarXiv:2402.18396

Deep Cost Ray Fusion for Sparse Depth Video Completion

Jungeon Kim, Soongjin Kim, Jaesik Park et al.

ECCV 2024posterarXiv:2409.14935

Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration

Xiong-Hui Chen, Junyin Ye, Hang Zhao et al.

ICML 2024poster

Deep Diffusion Image Prior for Efficient OOD Adaptation in 3D Inverse Problems

Hyungjin Chung, Jong Chul Ye

ECCV 2024posterarXiv:2407.10641
17
citations

Deep Equilibrium Diffusion Restoration with Parallel Sampling

Jiezhang Cao, Yue Shi, Kai Zhang et al.

CVPR 2024posterarXiv:2311.11600
23
citations

Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures

Zenan Ling, Longbo Li, Zhanbo Feng et al.

ICML 2024posterarXiv:2402.02697

Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss

Yahong Yang, Juncai He

ICML 2024posterarXiv:2402.00152

Deep Feature Surgery: Towards Accurate and Efficient Multi-Exit Networks

Cheng Gong, Yao Chen, Qiuyang Luo et al.

ECCV 2024posterarXiv:2407.13986
3
citations

Deep Fusion: Efficient Network Training via Pre-trained Initializations

Hanna Mazzawi, Xavi Gonzalvo, Michael Wunder et al.

ICML 2024posterarXiv:2306.11903

Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders

Emanuele Palumbo, Laura Manduchi, Sonia Laguna et al.

ICLR 2024poster

Deep Generative Model based Rate-Distortion for Image Downscaling Assessment

yuanbang liang, Bhavesh Garg, Paul L. Rosin et al.

CVPR 2024posterarXiv:2403.15139

Deep Imbalanced Regression via Hierarchical Classification Adjustment

Haipeng Xiong, Angela Yao

CVPR 2024posterarXiv:2310.17154
8
citations

Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations at Test-Time

Chiao-An Yang, Ziwei Liu, Raymond Yeh

ECCV 2024posterarXiv:2410.01083
1
citations

Deep Networks Always Grok and Here is Why

Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk

ICML 2024posterarXiv:2402.15555

DEEP NEURAL NETWORK INITIALIZATION WITH SPARSITY INDUCING ACTIVATIONS

Ilan Price, Nicholas Daultry Ball, Adam Jones et al.

ICLR 2024posterarXiv:2402.16184

Deep Neural Networks Tend To Extrapolate Predictably

Katie Kang, Amrith Setlur, Claire Tomlin et al.

ICLR 2024posterarXiv:2310.00873

Deep Neural Room Acoustics Primitive

Yuhang He, Anoop Cherian, Gordon Wichern et al.

ICML 2024poster