All Papers
34,598 papers found • Page 12 of 692
Conference
Additive Models Explained: A Computational Complexity Approach
Shahaf Bassan, Michal Moshkovitz, Guy Katz
Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models
Yoad Tewel, Rinon Gal, Dvir Samuel et al.
ADDQ: Adaptive distributional double Q-learning
Leif Döring, Benedikt Wille, Maximilian Birr et al.
Addressing Cold-Start Problem in Click-Through Rate Prediction via Supervised Diffusion Modeling
Wenqiao Zhu, Lulu Wang, Jun Wu
Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization
Emiliano Penaloza, Tianyue Zhang, Laurent Charlin et al.
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts
Lan Li, Da-Wei Zhou, Han-Jia Ye et al.
Addressing Label Shift in Distributed Learning via Entropy Regularization
Zhiyuan Wu, Changkyu Choi, Xiangcheng Cao et al.
Addressing Mark Imbalance in Integration-free Marked Temporal Point Processes
Sishun Liu, KE DENG, Yongli Ren et al.
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
Antoine Wehenkel, Juan L. Gamella, Ozan Sener et al.
Addressing Multi-Label Learning with Partial Labels: From Sample Selection to Label Selection
Gengyu Lyu, Bohang Sun, Xiang Deng et al.
Addressing Representation Collapse in Vector Quantized Models with One Linear Layer
Yongxin Zhu, Bocheng Li, Yifei Xin et al.
Addressing Text Embedding Leakage in Diffusion-based Image Editing
Sunung Mun, Jinhwan Nam, Sunghyun Cho et al.
A Decade's Battle on Dataset Bias: Are We There Yet?
Zhuang Liu, Kaiming He
A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization
Aron Brenner, Rahman Khorramfar, Jennifer Sun et al.
A deep inverse-mapping model for a flapping robotic wing
Hadar Sharvit, Raz Karl, Tsevi Beatus
A Deep Probabilistic Framework for Continuous Time Dynamic Graph Generation
Ryien Hosseini, Filippo Simini, Venkatram Vishwanath et al.
ADELA: Accelerating Evolutionary Design of Machine Learning Pipelines with the Accompanying Surrogate Model
Yang Gu, Jian Cao, Hengyu You et al.
ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
Pengwei Tang, Xiaolin Hu, Yong Liu
ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning
Zeyuan Liu, Zhihe Yang, Jiawei Xu et al.
AD-GS: Object-Aware B-Spline Gaussian Splatting for Self-Supervised Autonomous Driving
Jiawei Xu, Kai Deng, Zexin Fan et al.
ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization
Wenhao Shen, Wanqi Yin, Xiaofeng Yang et al.
Ad-Hoc Human-AI Coordination Challenge
Tin Dizdarevic, Ravi Hammond, Tobias Gessler et al.
Ad Hoc Teamwork via Offline Goal-Based Decision Transformers
Xinzhi Zhang, Hoehi Chan, Deheng Ye et al.
ADIEE: Automatic Dataset Creation and Scorer for Instruction-Guided Image Editing Evaluation
Sherry Chen, Yi Wei, Luowei Zhou et al.
A Difference-of-Convex Functions Approach to Energy-Based Iterative Reasoning
Daniel Tschernutter, David Diego Castro, Maciej Kasiński
A Differentiable Rank-Based Objective for Better Feature Learning
Krunoslav Lehman Pavasovic, Giulio Biroli, Levent Sagun
A Differentiable Wave Optics Model for End-to-End Computational Imaging System Optimization
Chi-Jui Ho, Yash Belhe, Steve Rotenberg et al.
A Differential and Pointwise Control Approach to Reinforcement Learning
Minh Nguyen, Chandrajit Bajaj
ADIFF: Explaining audio difference using natural language
Soham Deshmukh, Shuo Han, Rita Singh et al.
A Diffusion-Based Framework for Occluded Object Movement
Zheng-Peng Duan, Jiawei Zhang, Siyu Liu et al.
A Diffusion Model for Regular Time Series Generation from Irregular Data with Completion and Masking
Gal Fadlon, Idan Arbiv, Nimrod Berman et al.
ADIOS: Antibody Development via Opponent Shaping
Sebastian Towers, Aleksandra Kalisz, Philippe Robert et al.
A Distractor-Aware Memory for Visual Object Tracking with SAM2
Alan Lukezic, Jovana Videnović, Matej Kristan
A Distributional Approach to Uncertainty-Aware Preference Alignment Using Offline Demonstrations
Sheng Xu, Bo Yue, Hongyuan Zha et al.
Adjacent Words, Divergent Intents: Jailbreaking Large Language Models via Task Concurrency
Yukun Jiang, Mingjie Li, Michael Backes et al.
Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
Carles Domingo i Enrich, Michal Drozdzal, Brian Karrer et al.
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
Aaron Havens, Benjamin Kurt Miller, Bing Yan et al.
Adjoint Schrödinger Bridge Sampler
Guan-Horng Liu, Jaemoo Choi, Yongxin Chen et al.
Adjusted Count Quantification Learning on Graphs
Clemens Damke, Eyke Hüllermeier
Adjusting Initial Noise to Mitigate Memorization in Text-to-Image Diffusion Models
Hyeonggeun Han, Sehwan Kim, Hyungjun Joo et al.
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
Guiomar Pescador-Barrios, Sarah Filippi, Mark van der Wilk
Adjustment for Confounding using Pre-Trained Representations
Rickmer Schulte, David Rügamer, Thomas Nagler
AdMiT: Adaptive Multi-Source Tuning in Dynamic Environments
Xiangyu Chang, Fahim Faisal Niloy, Sk Miraj Ahmed et al.
ADMM for Nonconvex Optimization under Minimal Continuity Assumption
Ganzhao Yuan
ADMM for Structured Fractional Minimization
Ganzhao Yuan
ADMN: A Layer-Wise Adaptive Multimodal Network for Dynamic Input Noise and Compute Resources
Jason Wu, Yuyang Yuan, Kang Yang et al.
AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees
Yangning Li, Shaoshen Chen, Yinghui Li et al.
ADPretrain: Advancing Industrial Anomaly Detection via Anomaly Representation Pretraining
Xincheng Yao, Yan Luo, Zefeng Qian et al.
A Driving-Style-Adaptive Framework for Vehicle Trajectory Prediction
Di Wen, Yu Wang, Zhigang Wu et al.
AdsQA: Towards Advertisement Video Understanding
Xinwei Long, Kai Tian, Peng Xu et al.