Papers
Learning to LEAP: Efficient Dense Point Tracking by Focusing Where It Matters
Chenzhi Zhao, Wufan Wang, Bo Zhang et al.
Learning to Optimize Job Shop Scheduling Under Structural Uncertainty
Rui Zhang, Jianwei Niu, Xuefeng Liu et al.
Learning to Parse and Reconstruct: Bidirectional Modeling of Question-to-Program Mapping
Zeying Duan, Youtian Du, Yuanlin Chang et al.
Learning Topology-Aware Dynamic Associations for Robust Multi-Person Pose Estimation
Shengnan Hu, Yandong Liu, Jiangnan Liu et al.
Learning Topology-Driven Multi-Subspace Fusion for Grassmannian Deep Networks
Xuan Yu, Tianyang Xu
Learning to Rank: How GNNs Solve Max-Clique and Sparse PCA
Elad Shoham, Omri Haber, Havana Rika et al.
Learning to Select: Query-Aware Adaptive Dimension Selection for Dense Retrieval
Zhanyu Wu, Richong Zhang, Zhijie Nie
Learning to Tell Apart: Weakly Supervised Video Anomaly Detection via Disentangled Semantic Alignment
Wenti Yin, Huaxin Zhang, Xiang Wang et al.
Learning to Think on Hypergraph: HyperCoT for Structure-Guided N-ary Knowledge Graph Completion
Mengxue Yang, Jinming Li, Chun Yang et al.
Learning to Use AI for Learning: Teaching Responsible Use of AI Chatbot to K-12 Students Through an AI Literacy Module
Ruiwei Xiao, Xinying Hou, Ying-Jui Tseng et al.
Learning Uncertainty from Sequential Internal Dispersion in Large Language Models
Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen et al.
Learning Underwater Image Enhancement Iteratively Without Reference Images
Yi Tang, Hiroshi Kawasaki, Takafumi Iwaguchi et al.
Learning Unified Spatio-temporal Representations for Efficient Compressed Video Understanding
Shristi Das Biswas, Efstathia Soufleri, Arani Roy et al.
Learning Vision-Based Neural Network Controllers with Semi-Probabilistic Safety Guarantees
Xinhang Ma, Junlin Wu, Hussein Sibai et al.
Learning What Matters: Dynamic Dimension Selection and Aggregation for Interpretable Vision-Language Reward Modeling
Qiyuan Chen, Hongsen Huang, Jiahe Chen et al.
Learning What to Ignore: Mitigating Negative Transfer in Medical Knowledge Fusion via Clinical Task-Adaptive Selection
Xinyan Deng, Shoubin Dong, Xiaorou Zheng
Learning When to Personalize: LLM Based Playlist Generation via Query Taxonomy and Classification
Fedor Buzaev, Ivan Sukharev, Rinat Mullahmetov et al.
Learning While Staying Curious: Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models
Hao Wang, Hao Gu, Hongming Piao et al.
Learning Whom to Align With: Progressive Anomaly Combination Detection for Partially View-Aligned Clustering
Hang Gao, Zuosong Cai, Yuze Li et al.
Learning with Monotone Adversarial Corruptions
Kasper Green Larsen, Chirag Pabbaraju, Abhishek Shetty
Learning with Preserving for Continual Multitask Learning
Hanchen David Wang, Siwoo Bae, Zirong Chen et al.
Learning with Structure: Computing Consistent Subsets on Structurally-Regular Graphs
Aritra Banik, Mano Prakash Parthasarathi, Venkatesh Raman et al.
Learn Like Humans: Use Meta-cognitive Reflection for Efficient Self-Improvement
Xinmeng Hou, Bohao Qu, Wuqi Wang et al.
Learn to Relax with Large Language Models: Solving Constraint Optimization Problems via Bidirectional Coevolution
Beidan Liu, Zhengqiu Zhu, Chen Gao et al.