Table of Contents

• Sample Prior Guided Robust Model Learning to Suppress Noisy LabelsWenkai Chen, Chuang Zhu, Mengting Li. 3-19 [doi]
• DCID: Deep Canonical Information DecompositionAlexander Rakowski, Christoph Lippert. 20-35 [doi]
• Negative Prototypes Guided Contrastive Learning for Weakly Supervised Object DetectionYu Zhang, Chuang Zhu, Guoqing Yang, Siqi Chen. 36-51 [doi]
• Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream TasksHaiyan Zhao, Tianyi Zhou 0001, Guodong Long, Jing Jiang 0002, Chengqi Zhang. 52-68 [doi]
• Make a Long Image Short: Adaptive Token Length for Vision TransformersQiQi Zhou, Yichen Zhu. 69-85 [doi]
• Graph Rebasing and Joint Similarity Reconstruction for Cross-Modal Hash RetrievalDan Yao, Zhixin Li 0001. 86-102 [doi]
• ARConvL: Adaptive Region-Based Convolutional Learning for Multi-class Imbalance ClassificationShuxian Li, Liyan Song, Xiaoyu Wu, Zheng Hu, Yiu-ming Cheung, Xin Yao 0001. 103-120 [doi]
• Binary Domain Generalization for Sparsifying Binary Neural NetworksRiccardo Schiavone, Francesco Galati, Maria A. Zuluaga. 123-140 [doi]
• Efficient Hyperdimensional ComputingZhanglu Yan, Shida Wang, Kaiwen Tang, Weng-Fai Wong. 141-155 [doi]
• Rényi Divergence Deep Mutual LearningWeipeng Fuzzy Huang, Junjie Tao, Changbo Deng, Ming Fan, Wenqiang Wan, Qi Xiong, Guangyuan Piao. 156-172 [doi]
• Is My Neural Net Driven by the MDL Principle?Eduardo Brandao, Stefan Duffner, Rémi Emonet, Amaury Habrard, François Jacquenet, Marc Sebban. 173-189 [doi]
• Scoring Rule Nets: Beyond Mean Target Prediction in Multivariate RegressionDaan Roordink, Sibylle Hess. 190-205 [doi]
• Learning Distinct Features Helps, ProvablyFiras Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj. 206-222 [doi]
• Continuous Depth Recurrent Neural Differential EquationsSrinivas Anumasa, Geetakrishnasai Gunapati, P. K. Srijith. 223-238 [doi]
• Mitigating Algorithmic Bias with Limited AnnotationsGuanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu. 241-258 [doi]
• 2AN: Fairness-Aware Graph Generative Adversarial NetworksZichong Wang, Charles Wallace 0001, Albert Bifet, Xin Yao, Wenbin Zhang 0002. 259-275 [doi]
• Targeting the Source: Selective Data Curation for Debiasing NLP ModelsYacine Gaci, Boualem Benatallah, Fabio Casati, Khalid Benabdeslem. 276-294 [doi]
• Fairness in Multi-Task Learning via Wasserstein BarycentersFrançois Hu, Philipp Ratz, Arthur Charpentier. 295-312 [doi]
• REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse TrainingJiaxu Zhao, Lu Yin 0006, Shiwei Liu, Meng Fang, Mykola Pechenizkiy. 313-329 [doi]
• How to Overcome Confirmation Bias in Semi-Supervised Image Classification by Active LearningSandra Gilhuber, Rasmus Hvingelby, Mang Ling Ada Fok, Thomas Seidl 0001. 330-347 [doi]
• Towards Practical Federated Causal Structure LearningZhaoyu Wang, Pingchuan Ma 0004, Shuai Wang 0011. 351-367 [doi]
• Triplets Oversampling for Class Imbalanced Federated DatasetsChenguang Xiao, Shuo Wang 0005. 368-383 [doi]
• Learning Fast and Slow: Towards Inclusive Federated LearningMuhammad Tahir Munir, Muhammad Mustansar Saeed, Mahad Ali, Zafar Ayyub Qazi, Agha Ali Raza, Ihsan Ayyub Qazi. 384-401 [doi]
• Practical and General Backdoor Attacks Against Vertical Federated LearningYuexin Xuan, Xiaojun Chen 0004, Zhendong Zhao, Bisheng Tang, Ye Dong. 402-417 [doi]
• Not All Tasks Are Equal: A Parameter-Efficient Task Reweighting Method for Few-Shot LearningXin Liu, Yilin Lyu, Liping Jing, Tieyong Zeng, Jian Yu. 421-437 [doi]
• Boosting Generalized Few-Shot Learning by Scattering Intra-class DistributionYunlong Yu, Lisha Jin, Yingming Li. 438-453 [doi]
• vMF Loss: Exploring a Scattered Intra-class Hypersphere for Few-Shot LearningXin Liu, Shijing Wang, Kairui Zhou, Yilin Lyu, MingYang Song, Liping Jing, Tieyong Zeng, Jian Yu. 454-470 [doi]
• Meta-HRNet: A High Resolution Network for Coarse-to-Fine Few-Shot ClassificationZhaochen Li, Kedian Mu. 471-487 [doi]
• MuSE: A Multi-scale Emotional Flow Graph Model for Empathetic Dialogue GenerationDeji Zhao, Donghong Han, Ye Yuan 0001, Chao Wang 0057, Shuangyong Song. 491-507 [doi]
• Posterior Consistency for Missing Data in Variational AutoencodersTimur Sudak, Sebastian Tschiatschek. 508-524 [doi]
• KnowPrefix-Tuning: A Two-Stage Prefix-Tuning Framework for Knowledge-Grounded Dialogue GenerationJiaqi Bai, Zhao Yan, Ze Yang 0001, Jian Yang, Xinnian Liang, Hongcheng Guo, Zhoujun Li 0001. 525-542 [doi]
• Learning Data Representations with Joint Diffusion ModelsKamil Deja, Tomasz Trzcinski, Jakub M. Tomczak. 543-559 [doi]
• MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule GenerationClément Vignac, Nagham Osman, Laura Toni, Pascal Frossard. 560-576 [doi]
• Cold-Start Multi-hop Reasoning by Hierarchical Guidance and Self-verificationMayi Xu, Ke Sun 0010, Yongqi Li 0002, Tieyun Qian. 577-592 [doi]
• Efficient Fine-Tuning Large Language Models for Knowledge-Aware Response PlanningMinh Nguyen, Kishan K. C., Toan Nguyen, Ankit Chadha, Thuy Vu. 593-611 [doi]
• Attentive Multi-Layer Perceptron for Non-autoregressive GenerationShuyang Jiang, Jun Zhang, JiangTao Feng, Lin Zheng, Lingpeng Kong. 612-629 [doi]
• MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders Are Better Dense RetrieversKun Zhou, Xiao Liu 0029, Yeyun Gong, Wayne Xin Zhao, Daxin Jiang, Nan Duan, Ji-Rong Wen. 630-647 [doi]
• Duplicate Multi-modal Entities Detection with Graph Contrastive Self-training NetworkShuyun Gu, Xiao Wang 0017, Chuan Shi. 651-665 [doi]
• Graph Contrastive Representation Learning with Input-Aware and Cluster-Aware RegularizationJin Li, Bingshi Li, Qirong Zhang, Xinlong Chen, Xinyang Huang, Longkun Guo, Yang-Geng Fu. 666-682 [doi]
• Temporal Graph Representation Learning with Adaptive Augmentation ContrastiveHongjiang Chen, Pengfei Jiao, Huijun Tang, Huaming Wu. 683-699 [doi]
• Hierarchical Graph Contrastive LearningHao Yan, Senzhang Wang, Jun Yin, Chaozhuo Li, Junxing Zhu, Jianxin Wang. 700-715 [doi]