2024 Poster Papers
8,865 papers found • Page 16 of 178
Barrier Algorithms for Constrained Non-Convex Optimization
Pavel Dvurechenskii, Mathias Staudigl
BA-SAM: Scalable Bias-Mode Attention Mask for Segment Anything Model
song yiran, Qianyu Zhou, Xiangtai Li et al.
BaSIC: BayesNet Structure Learning for Computational Scalable Neural Image Compression
Yufeng Zhang, Hang Yu, Shizhan Liu et al.
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
Han Zhou, Xingchen Wan, Lev Proleev et al.
Batched Low-Rank Adaptation of Foundation Models
Yeming Wen, Swarat Chaudhuri
Batch Normalization Alleviates the Spectral Bias in Coordinate Networks
Zhicheng Cai, Hao Zhu, Qiu Shen et al.
Batch normalization is sufficient for universal function approximation in CNNs
Rebekka Burkholz
BatchPrompt: Accomplish more with less
Jianzhe Lin, Maurice Diesendruck, Liang Du et al.
Batch Singular Value Polarization and Weighted Semantic Augmentation for Universal Domain Adaptation
Ziqi Wang, Wei Wang, Chao Huang et al.
BAT: Learning to Reason about Spatial Sounds with Large Language Models
Zhisheng Zheng, Puyuan Peng, Ziyang Ma et al.
Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual Information
Linfeng Ye, Shayan Mohajer Hamidi, Renhao Tan et al.
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference
Siqi Kou, Lei Gan, Dequan Wang et al.
Bayesian Adaptation of Network Depth and Width for Continual Learning
Jeevan Thapa, Rui Li
Bayesian Coreset Optimization for Personalized Federated Learning
Prateek Chanda, Shrey Modi, Ganesh Ramakrishnan
Bayesian Design Principles for Offline-to-Online Reinforcement Learning
Hao Hu, yiqin yang, Jianing Ye et al.
Bayesian Detector Combination for Object Detection with Crowdsourced Annotations
Zhi Qin Tan, Olga Isupova, Gustavo Carneiro et al.
Bayesian Differentiable Physics for Cloth Digitalization
Deshan Gong, Ningtao Mao, He Wang
Bayesian Diffusion Models for 3D Shape Reconstruction
Haiyang Xu, Yu lei, Zeyuan Chen et al.
Bayesian Evidential Deep Learning for Online Action Detection
Hongji Guo, Hanjing Wang, Qiang Ji
Bayesian Exploration Networks
Mattie Fellows, Brandon Kaplowitz, Christian Schroeder de Witt et al.
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification
Yibo Miao, Yu lei, Feng Zhou et al.
Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification
Luyang Fang, Yongkai Chen, Wenxuan Zhong et al.
Bayesian Low-rank Adaptation for Large Language Models
Adam Yang, Maxime Robeyns, Xi Wang et al.
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation
Konstantin Hess, Valentyn Melnychuk, Dennis Frauen et al.
Bayesian Optimization of Function Networks with Partial Evaluations
Poompol Buathong, Jiayue Wan, Raul Astudillo et al.
Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models
Ding Huang, Ting Li, Jian Huang
Bayesian Program Learning by Decompiling Amortized Knowledge
Alessandro Palmarini, Christopher Lucas, Siddharth N
Bayesian Regret Minimization in Offline Bandits
Marek Petrik, Guy Tennenholtz, Mohammad Ghavamzadeh
Bayesian Self-Training for Semi-Supervised 3D Segmentation
Ozan Unal, Christos Sakaridis, Luc Van Gool
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning
Idan Achituve, Idit Diamant, Arnon Netzer et al.
BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
Jiangmeng Li, Fei Song, Yifan Jin et al.
BEAF: Observing BEfore-AFter Changes to Evaluate Hallucination in Vision-language Models
Ye-Bin Moon, Nam Hyeon-Woo, Wonseok Choi et al.
Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design
Jeff Guo, Philippe Schwaller
Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
Iosif Sakos, Stefanos Leonardos, Stelios Stavroulakis et al.
Beat-It: Beat-Synchronized Multi-Condition 3D Dance Generation
Zikai Huang, Xuemiao Xu, Cheng Xu et al.
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference
Haoxuan Li, Chunyuan Zheng, Sihao Ding et al.
Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
Lukas Struppek, Dominik Hintersdorf, Kristian Kersting
BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
Daeun Lee, Jaehong Yoon, Sung Ju Hwang
Behaviour Distillation
Andrei Lupu, Chris Lu, Jarek Liesen et al.
Behind the Veil: Enhanced Indoor 3D Scene Reconstruction with Occluded Surfaces Completion
Su Sun, Cheng Zhao, Yuliang Guo et al.
Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations
Xiaolin Sun, Zizhan Zheng
Bellman Optimal Stepsize Straightening of Flow-Matching Models
Bao Nguyen, Binh Nguyen, Viet Anh Nguyen
BEM: Balanced and Entropy-based Mix for Long-Tailed Semi-Supervised Learning
Hongwei Zheng, Linyuan Zhou, Han Li et al.
Be More Active! Understanding the Differences Between Mean and Sampled Representations of Variational Autoencoders
Lisa Bonheme, Marek Grzes
BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Models
Rizhao Cai, Zirui Song, DAYAN GUAN et al.
Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT
Jon Saad-Falcon, Daniel Y Fu, Simran Arora et al.
Benchmarking and Improving Generator-Validator Consistency of Language Models
XIANG LI, Vaishnavi Shrivastava, Siyan Li et al.
Benchmarking Audio Visual Segmentation for Long-Untrimmed Videos
Chen Liu, Peike Li, Qingtao Yu et al.
Benchmarking Deletion Metrics with the Principled Explanations
Yipei Wang, Xiaoqian Wang
Benchmarking Implicit Neural Representation and Geometric Rendering in Real-Time RGB-D SLAM
Tongyan Hua, Addison, Lin Wang