Poster Papers
24,624 papers found • Page 61 of 493
Conference
Data Selection Matters: Towards Robust Instruction Tuning of Large Multimodal Models
Xu Yang, Chen Liu, Ying Wei
Data Selection via Optimal Control for Language Models
Yuxian Gu, Li Dong, Hongning Wang et al.
Dataset Distillation as Data Compression: A Rate-Utility Perspective
Youneng Bao, Yiping Liu, Zhuo Chen et al.
Dataset Distillation for Pre-Trained Self-Supervised Vision Models
George Cazenavette, Antonio Torralba, Vincent Sitzmann
Dataset Distillation of 3D Point Clouds via Distribution Matching
Jae-Young Yim, Dongwook Kim, Jae-Young Sim
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks
Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman
Dataset Distillation via the Wasserstein Metric
Haoyang Liu, Peiran Wang, Yijiang Li et al.
Dataset Ownership Verification for Pre-trained Masked Models
Yuechen Xie, Jie Song, Yicheng Shan et al.
Dataset Ownership Verification in Contrastive Pre-trained Models
Yuechen Xie, Jie Song, Mengqi Xue et al.
Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality
Alex Fang, Hadi Pouransari, Matt Jordan et al.
Data Shapley in One Training Run
Jiachen (Tianhao) Wang, Prateek Mittal, Dawn Song et al.
DataSIR: A Benchmark Dataset for Sensitive Information Recognition
Fan Mo, Bo Liu, Yuan Fan et al.
Data Synthesis with Diverse Styles for Face Recognition via 3DMM-Guided Diffusion
Yuxi Mi, Zhizhou Zhong, Yuge Huang et al.
Data Taggants: Dataset Ownership Verification Via Harmless Targeted Data Poisoning
Wassim Bouaziz, Nicolas Usunier, El-Mahdi El-Mhamdi
Data Unlearning in Diffusion Models
Silas Alberti, Kenan Hasanaliyev, Manav Shah et al.
DATE-LM: Benchmarking Data Attribution Evaluation for Large Language Models
Cathy Jiao, Yijun Pan, Emily Xiao et al.
D-Attn: Decomposed Attention for Large Vision-and-Language Model
Chia-Wen Kuo, Sijie Zhu, Fan Chen et al.
DAVE: Diagnostic benchmark for Audio Visual Evaluation
Gorjan Radevski, Teodora Popordanoska, Matthew Blaschko et al.
David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training
Weijian Luo, colin zhang, Debing Zhang et al.
DAViD: Data-efficient and Accurate Vision Models from Synthetic Data
Fatemeh Saleh, Sadegh Aliakbarian, Charlie Hewitt et al.
DAViD: Modeling Dynamic Affordance of 3D Objects Using Pre-trained Video Diffusion Models
Hyeonwoo Kim, Sangwon Baik, Hanbyul Joo
DA-VPT: Semantic-Guided Visual Prompt Tuning for Vision Transformers
Li Ren, Chen Chen, Liqiang Wang et al.
DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
Changdae Oh, Yixuan Li, Kyungwoo Song et al.
DAWN: Dynamic Frame Avatar with Non-autoregressive Diffusion Framework for Talking head Video Generation
Hanbo Cheng, Limin Lin, Chenyu Liu et al.
DBLoss: Decomposition-based Loss Function for Time Series Forecasting
Xiangfei Qiu, Xingjian Wu, Hanyin Cheng et al.
DC4GS: Directional Consistency-Driven Adaptive Density Control for 3D Gaussian Splatting
Moonsoo Jeong, Dongbeen Kim, Minseong Kim et al.
DCAD-2000: A Multilingual Dataset across 2000+ Languages with Data Cleaning as Anomaly Detection
Yingli Shen, Wen Lai, Shuo Wang et al.
DC-AE 1.5: Accelerating Diffusion Model Convergence with Structured Latent Space
Junyu Chen, Dongyun Zou, Wenkun He et al.
DCA: Graph-Guided Deep Embedding Clustering for Brain Atlases
Mo WANG, Kaining Peng, Jingsheng Tang et al.
DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer
Yecheng Wu, Han Cai, Junyu Chen et al.
DCBM: Data-Efficient Visual Concept Bottleneck Models
Katharina Prasse, Patrick Knab, Sascha Marton et al.
DC-ControlNet: Decoupling Inter- and Intra-Element Conditions in Image Generation with Diffusion Models
hongji yang, Wencheng Han, Yucheng Zhou et al.
DCEvo: Discriminative Cross-Dimensional Evolutionary Learning for Infrared and Visible Image Fusion
Jinyuan Liu, Bowei Zhang, Qingyun Mei et al.
DCHM: Depth-Consistent Human Modeling for Multiview Detection
Jiahao Ma, Tianyu Wang, Miaomiao Liu et al.
DCI: Dual-Conditional Inversion for Boosting Diffusion-Based Image Editing
Zixiang Li, Haoyu Wang, Wei Wang et al.
DCT-CryptoNets: Scaling Private Inference in the Frequency Domain
Arjun Roy, Kaushik Roy
DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space
Mang Ning, Mingxiao Li, Jianlin Su et al.
DC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation
Jihun Kim, Hoyong Kwon, Hyeokjun Kweon et al.
DDB: Diffusion Driven Balancing to Address Spurious Correlations
Aryan Yazdan Parast, Basim Azam, Naveed Akhtar
De^2Gaze: Deformable and Decoupled Representation Learning for 3D Gaze Estimation
Yunfeng Xiao, Xiaowei Bai, Baojun Chen et al.
DEAL: Data-Efficient Adversarial Learning for High-Quality Infrared Imaging
Zhu Liu, Zijun Wang, Jinyuan Liu et al.
DEAL: Diffusion Evolution Adversarial Learning for Sim-to-Real Transfer
Wentao Xu, Huiqiao Fu, Haoyu Dong et al.
DEALing with Image Reconstruction: Deep Attentive Least Squares
Mehrsa Pourya, Erich Kobler, Michael Unser et al.
De-AntiFake: Rethinking the Protective Perturbations Against Voice Cloning Attacks
Wei Fan, Kejiang Chen, Chang Liu et al.
DebGCD: Debiased Learning with Distribution Guidance for Generalized Category Discovery
Yuanpei Liu, Kai Han
Debiased Curriculum Adaptation for Safe Transfer Learning in Chest X-ray Classification
Mingyang Liu, Xinyang Chen, Yang Shu et al.
Debiased Teacher for Day-to-Night Domain Adaptive Object Detection
Yiming Cui, Liang Li, Haibing YIN et al.
Debiasing Federated Learning with Correlated Client Participation
Zhenyu Sun, Ziyang Zhang, Zheng Xu et al.
Debiasing Mini-Batch Quadratics for Applications in Deep Learning
Lukas Nicola Tatzel, Bálint Mucsányi, Osane Hackel et al.
Debiasing Multimodal Large Language Models via Noise-Aware Preference Optimization
zefeng zhang, Hengzhu Tang, Jiawei Sheng et al.