Papers
11,015 papers found
CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling
Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley et al.
CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception
Jiachen Sun, Haizhong Zheng, Qingzhao Zhang et al.
CAMBranch: Contrastive Learning with Augmented MILPs for Branching
Jiacheng Lin, Meng XU, Zhihua Xiong et al.
Cameras as Rays: Pose Estimation via Ray Diffusion
Jason Y. Zhang, Amy Lin, Moneish Kumar et al.
CAMIL: Context-Aware Multiple Instance Learning for Cancer Detection and Subtyping in Whole Slide Images
Olga Fourkioti, Matt De Vries, Chris Bakal
Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning
Shuo He, Chaojie Wang, Guowu Yang et al.
Can Large Language Models Infer Causation from Correlation?
Zhijing Jin, Jiarui Liu, Zhiheng LYU et al.
Can LLM-Generated Misinformation Be Detected?
Canyu Chen, Kai Shu
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
Miao Xiong, Zhiyuan Hu, Xinyang Lu et al.
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory
Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou et al.
Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks
Vaidehi Patil, Peter Hase, Mohit Bansal
Can Transformers Capture Spatial Relations between Objects?
Chuan Wen, Dinesh Jayaraman, Yang Gao
Can We Evaluate Domain Adaptation Models Without Target-Domain Labels?
Jianfei Yang, Hanjie Qian, Yuecong Xu et al.
Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision?
Gourav Datta, Zeyu Liu, Peter Anthony Beerel
CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting
Xue Wang, Tian Zhou, Qingsong Wen et al.
CAS: A Probability-Based Approach for Universal Condition Alignment Score
Chunsan Hong, ByungHee Cha, Tae-Hyun Oh
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation
Yangsibo Huang, Samyak Gupta, Mengzhou Xia et al.
Cauchy-Schwarz Divergence Information Bottleneck for Regression
Shujian Yu, Xi Yu, Sigurd Løkse et al.
Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
Maresa Schröder, Dennis Frauen, Stefan Feuerriegel
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder
Ziqi Xu, Debo Cheng, Jiuyong Li et al.
Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks
Kesen Zhao, Liang Zhang
CausalLM is not optimal for in-context learning
Nan Ding, Tomer Levinboim, Jialin Wu et al.
Causally Aligned Curriculum Learning
Mingxuan Li, Junzhe Zhang, Elias Bareinboim
Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning
Ahmed Abdulaal, adamos hadjivasiliou, Nina Montana-Brown et al.