Papers
ConStruct: Structural Distillation of Foundation Models for Prototype-Based Weakly Supervised Histopathology Segmentation
Khang Le, Ha Thach, Anh M. Vu et al.
ConSurv: Multimodal Continual Learning for Survival Analysis
Dianzhi Yu, Conghao Xiong, Yankai Chen et al.
Content-aware Information Compression and Selection for Whole Slide Image Analysis
Tingting Zheng, Hongxun Yao, Sicheng Zhao et al.
Content Diversity-guided Ambiguity Mitigation for Open-Set Noisy Label Learning
Zhihao Zhou, Rui Li, Xueying Li
Context-Aware Diffusion for Telemetry Time Series with Permutation-Stable Feature Modeling (Student Abstract)
Giovanni B. Esposito, Daniele Cesarini, Andrea Bartolini
Context-aware Dynamic Contrastive Learning Network and E-Bike Rider Benchmark for Person Search
Hongchao Li, Chengcheng Li, Xixi Wang et al.
Context-aware Graph Meta-learning
Ningbo Huang, Gang Zhou, Meng Zhang et al.
Context-Aware Patch Representations for Multiple Instance Learning
Andreas Lolos, Theofilos Christodoulou, Aris L. Moustakas et al.
ContextFlow: Training-Free Video Object Editing via Adaptive Context Enrichment
Yiyang Chen, Xuanhua He, Xiujun Ma et al.
ContextGraph: Lifelog Intelligence Framework for Contextual Subgraph Evolution
Anil Sharma, Gunturi Venkata Sai Phani Kiran, Jayesh Rajkumar Vachhani et al.
ContextLens: Modeling Imperfect Privacy and Safety Context for Legal Compliance
Haoran Li, Yulin Chen, Huihao Jing et al.
Context-Preserving Dermoscopic Editing: Mask-Guided Lesion-Aware Diffusion for Attribute Modification
Tao Sun, Yun Jiang, Yarong Jin et al.
Context Selection and Rewriting for Video-based Educational Question Generation
Mengxia Yu, Bang Nguyen, Olivia Zino et al.
Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions
Rashmeet Kaur Nayyar, Naman Shah, Siddharth Srivastava
Contextual Diversity Measure (CDM) for Controllable Story Generation in Large Language Models
Richard Susilo, Hanna Suominen, Patrik Haslum
Contextual morphologically-guided tokenization for Latin encoder models
Marisa Hudspeth, Patrick J. Burns, Brendan O'Connor
Contextual Relevance and Adaptive Sampling for LLM-Based Document Reranking
Jerry Huang, Siddarth Madala, Cheng Niu et al.
Context Volume Drives Performance: Tackling Domain Shift in Extremely Low-Resource Translation via RAG
David Samuel Setiawan, Raphaël Merx, Jey Han Lau
Continual-learning for Modelling Low-Resource Languages from Large Language Models
Santosh Srinath K, Mudit Somani, Varun Reddy Padala et al.
Continual Neural Topic Model
Charu Karakkaparambil James, Waleed Mustafa, Marcio Monteiro et al.
Continual Out-of-Distribution Detection with Analytic Neural Collapse
Saleh Momeni, Changnan Xiao, Bing Liu
Continual Pretraining on Encrypted Synthetic Data for Privacy-Preserving LLMs
Honghao Liu, Xuhui Jiang, Chengjin Xu et al.
Continuous Context Sampling Allows Extending Diversity Boundaries of Large Language Models
Mateusz Bystroński, Doheon Han, Nitesh V. Chawla et al.
Continuous Degradation Modeling via Latent Flow Matching for Real-World Super-Resolution
Hyeonjae Kim, Dongjin Kim, Eugene Jin et al.