Papers
11,951 papers found
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.
CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting
Jiezhi Yang, Khushi P Desai, Charles Packer 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 Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models
Álvaro Ribot, Chandler Squires, Caroline Uhler
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.
Causal-StoNet: Causal Inference for High-Dimensional Complex Data
Yaxin Fang, Faming Liang
Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions
Xiu-Chuan Li, Kun Zhang, Tongliang Liu
Causal Subgraphs and Information Bottlenecks: Redefining OOD Robustness in Graph Neural Networks
Weizhi An, Wenliang Zhong, Feng Jiang et al.
CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery
Yuxiao Cheng, Ziqian Wang, Tingxiong Xiao et al.