Papers
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Chenlu Ye, Yujia Jin, Alekh Agarwal et al.
CATP-LLM: Empowering Large Language Models for Cost-Aware Tool Planning
Duo Wu, Jinghe Wang, Yuan Meng et al.
CAT-SG: A Large Dynamic Scene Graph Dataset for Fine-Grained Understanding of Cataract Surgery
Felix Holm, Gözde Ünver, Ghazal Ghazaei et al.
CATSplat: Context-Aware Transformer with Spatial Guidance for Generalizable 3D Gaussian Splatting from A Single-View Image
Wonseok Roh, Hwanhee Jung, Jong Wook Kim et al.
CATVis: Context-Aware Thought Visualization
Tariq Mehmood, Hamza Ahmad, Muhammad Haroon Shakeel et al.
CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models
Zheng Chong, Xiao Dong, Haoxiang Li et al.
Cauchy Diffusion: A Heavy-tailed Denoising Diffusion Probabilistic Model for Speech Synthesis
Qi Lian, Yu Qi, Yueming Wang
Cauchy-Schwarz Regularizers
Sueda Taner, Ziyi Wang, Christoph Studer
CAUDA-MI: Cross Attention-Guided Unsupervised Domain Adaptation with Mutual Information for Cardiac MRI Segmentation
Dianrong Du, Hengfei Cui, Jiatong Li et al.
CausalAbstain: Enhancing Multilingual LLMs with Causal Reasoning for Trustworthy Abstention
Yuxi Sun, Aoqi Zuo, Wei Gao et al.
Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability
Atticus Geiger, Duligur Ibeling, Amir Zur et al.
Causal Abstraction Inference under Lossy Representations
Kevin Muyuan Xia, Elias Bareinboim
Causal Abstraction Learning based on the Semantic Embedding Principle
Gabriele D’Acunto, Fabio Massimo Zennaro, Yorgos Felekis et al.
Causal Attribution Analysis for Continuous Outcomes
Shanshan Luo, Yu Yixuan, Chunchen Liu et al.
Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Acting
Wei Chen, Jiahao Zhang, Haipeng Zhu et al.
Causal Bandits without Graph Learning
Mikhail Konobeev, Jalal Etesami, Negar Kiyavash
Causal Composition Diffusion Model for Closed-loop Traffic Generation
Haohong Lin, Xin Huang, Tung Phan et al.
Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning
Gabriele Dominici, Pietro Barbiero, Mateo Espinosa Zarlenga et al.
Causal Denoising Prototypical Network for Few-Shot Multi-label Aspect Category Detection
Jin Cui, Xinfeng Wang, Yoshimi Suzuki et al.
Causal Discovery by Interventions via Integer Programming
Abdelmonem Elrefaey, Rong Pan
Causal Discovery-Driven Change Point Detection in Time Series
Shanyun Gao, Raghavendra Addanki, Tong Yu et al.
Causal Discovery for Linear Non-Gaussian Models with Disjoint Cycles
Mathias Drton, Marina Garrote-López, Niko Nikov et al.
Causal Discovery from Conditionally Stationary Time Series
Carles Balsells-Rodas, Xavier Sumba, Tanmayee Narendra et al.
Causal discovery in mixed additive noise models
Ruicong Yao, Tim Verdonck, Jakob Raymaekers
Causal Discovery on Dependent Binary Data
Alex Chen, Qing Zhou