Poster Papers
24,624 papers found • Page 9 of 493
ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization
Wenhao Shen, Wanqi Yin, Xiaofeng Yang 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 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.
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.
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.
AdsQA: Towards Advertisement Video Understanding
Xinwei Long, Kai Tian, Peng Xu et al.
ADU: Adaptive Detection of Unknown Categories in Black-Box Domain Adaptation
Yushan Lai, Guowen Li, Haoyuan Liang et al.
A duality framework for analyzing random feature and two-layer neural networks
Hongrui Chen, Jihao Long, Lei Wu
AdvAgent: Controllable Blackbox Red-teaming on Web Agents
Chejian Xu, Mintong Kang, Jiawei Zhang et al.
Advancing Adversarial Robustness in GNeRFs: The IL2-NeRF Attack
Nicole Meng, Caleb Manicke, Ronak Sahu et al.
Advancing Compositional Awareness in CLIP with Efficient Fine-Tuning
Amit Peleg, Naman Deep Singh, Matthias Hein
Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
Davide Sartor, Alberto Sinigaglia, Gian Antonio Susto
Advancing Generalizable Tumor Segmentation with Anomaly-Aware Open-Vocabulary Attention Maps and Frozen Foundation Diffusion Models
Yankai Jiang, Peng Zhang, Donglin Yang et al.
Advancing Graph Generation through Beta Diffusion
Xinyang Liu, Yilin He, Bo Chen et al.
Advancing Interpretability of CLIP Representations with Concept Surrogate Model
Nhat Hoang-Xuan, Xiyuan Wei, Wanli Xing et al.
Advancing LLM Reasoning Generalists with Preference Trees
Lifan Yuan, Ganqu Cui, Hanbin Wang et al.
Advancing Machine-Generated Text Detection from an Easy to Hard Supervision Perspective
Chenwang Wu, Yiu-ming Cheung, Bo Han et al.
Advancing Manga Analysis: Comprehensive Segmentation Annotations for the Manga109 Dataset
Minshan Xie, Jian Lin, Hanyuan Liu et al.
Advancing Mathematical Reasoning in Language Models: The Impact of Problem-Solving Data, Data Synthesis Methods, and Training Stages
Zui Chen, Tianqiao Liu, Tongqing et al.
Advancing Myopia To Holism: Fully Contrastive Language-Image Pre-training
Haicheng Wang, Chen Ju, Weixiong Lin et al.
Advancing Out-of-Distribution Detection via Local Neuroplasticity
Alessandro Canevaro, Julian Schmidt, Sajad Marvi et al.
Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge
Hanglei Hu, Yingying Guo, Zhikang Chen et al.
Advancing Prompt-Based Methods for Replay-Independent General Continual Learning
Zhiqi KANG, Liyuan Wang, Xingxing Zhang et al.
Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers
Efstathios Karypidis, Ioannis Kakogeorgiou, Spyros Gidaris et al.
Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation
Yu Lei, Bingde Liu, Qingsong Xie et al.
Advancing Textual Prompt Learning with Anchored Attributes
Zheng Li, Yibing Song, Ming-Ming Cheng et al.
Advancing Visual Large Language Model for Multi-granular Versatile Perception
Wentao Xiang, Haoxian Tan, Cong Wei et al.
Advancing Wasserstein Convergence Analysis of Score-Based Models: Insights from Discretization and Second-Order Acceleration
Yifeng Yu, Lu Yu
Advantage Alignment Algorithms
Juan Duque, Milad Aghajohari, Timotheus Cooijmans et al.
Advantage-Guided Distillation for Preference Alignment in Small Language Models
Shiping Gao, Fanqi Wan, Jiajian Guo et al.
Adv-CPG: A Customized Portrait Generation Framework with Facial Adversarial Attacks
Junying Wang, Hongyuan Zhang, Yuan Yuan