Poster Papers
24,624 papers found • Page 41 of 493
Conference
CAT: Content-Adaptive Image Tokenization
Junhong Shen, Kushal Tirumala, Michihiro Yasunaga et al.
CAT: Contrastive Adversarial Training for Evaluating the Robustness of Protective Perturbations in Latent Diffusion Models
Sen Peng, Mingyue Wang, Jianfei He et al.
Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics
Tyler Kastner, Mark Rowland, Yunhao Tang et al.
Categorical Schrödinger Bridge Matching
Grigoriy Ksenofontov, Aleksandr Korotin
Category-Agnostic Neural Object Rigging
Guangzhao He, Chen Geng, Shangzhe Wu et al.
Category-Specific Selective Feature Enhancement for Long-Tailed Multi-Label Image Classification
Ruiqi Du, Xu Tang, Xiangrong Zhang et al.
CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration
Haoyun Jiang, Haolin li, jianwei zhang et al.
CAT Merging: A Training-Free Approach for Resolving Conflicts in Model Merging
Wenju Sun, Qingyong Li, Yangliao Geng et al.
CATP-LLM: Empowering Large Language Models for Cost-Aware Tool Planning
Duo Wu, Jinghe Wang, Yuan Meng et al.
CATransformers: Carbon Aware Transformers Through Joint Model-Hardware Optimization
Irene Wang, Mostafa Elhoushi, H Ekin Sumbul et al.
CATSplat: Context-Aware Transformer with Spatial Guidance for Generalizable 3D Gaussian Splatting from A Single-View Image
Wonseok Roh, Hwanhee Jung, JongWook Kim et al.
CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models
Zheng Chong, Xiao Dong, Haoxiang Li et al.
Cauchy-Schwarz Regularizers
Sueda Taner, Ziyi Wang, Christoph Studer
Causal Abstraction Inference under Lossy Representations
Kevin Xia, Elias Bareinboim
Causal Abstraction Learning based on the Semantic Embedding Principle
Gabriele DAcunto, Fabio Massimo Zennaro, Yorgos Felekis et al.
Causal Climate Emulation with Bayesian Filtering
Sebastian H. M. Hickman, Ilija Trajković, Julia Kaltenborn et al.
Causal Composition Diffusion Model for Closed-loop Traffic Generation
Haohong Lin, Xin Huang, Tung Phan-Minh et al.
Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning
Gabriele Dominici, Pietro Barbiero, Mateo Espinosa Zarlenga et al.
Causal Discovery and Inference through Next-Token Prediction
Eivinas Butkus, Nikolaus Kriegeskorte
Causal Discovery from Conditionally Stationary Time Series
Carles Balsells-Rodas, Xavier Sumba, Tanmayee Narendra et al.
Causal Discovery over Clusters of Variables in Markovian Systems
Tara Anand, Adèle Ribeiro, Jin Tian et al.
Causal Discovery via Bayesian Optimization
Bao Duong, Sunil Gupta, Thin Nguyen
Causal Disentanglement and Cross-Modal Alignment for Enhanced Few-Shot Learning
Tianjiao Jiang, Zhen Zhang, Yuhang Liu et al.
CausalDynamics: A large‐scale benchmark for structural discovery of dynamical causal models
Benjamin Herdeanu, Juan Nathaniel, Carla Roesch et al.
Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables
Yaochen Zhu, Jing Ma, Liang Wu et al.
Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants
Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar et al.
Causal-Entity Reflected Egocentric Traffic Accident Video Synthesis
Lei-lei Li, Jianwu Fang, Junbin Xiao et al.
Causal Explanation-Guided Learning for Organ Allocation
Alessandro Marchese, Jeroen Berrevoets, Sam Verboven
Causal Graphical Models for Vision-Language Compositional Understanding
Fiorenzo Parascandolo, Nicholas Moratelli, Enver Sangineto et al.
Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference
Anpeng Wu, Haiyi Qiu, Zhengming Chen et al.
Causal Head Gating: A Framework for Interpreting Roles of Attention Heads in Transformers
Andrew Nam, Henry Conklin, Yukang Yang et al.
Causal Identification for Complex Functional Longitudinal Studies
Andrew Ying
Causal Information Prioritization for Efficient Reinforcement Learning
Hongye Cao, Fan Feng, Tianpei Yang et al.
Causal Invariance-aware Augmentation for Brain Graph Contrastive Learning
Minqi Yu, Jinduo Liu, Junzhong Ji
Causality-Aware Contrastive Learning for Robust Multivariate Time-Series Anomaly Detection
HyunGi Kim, Jisoo Mok, Dong Jun Lee et al.
Causality-guided Prompt Learning for Vision-language Models via Visual Granulation
Mengyu Gao, Qiulei Dong
Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features
Kaichen Xu, Yihang Du, Mianpeng Liu et al.
Causality Inspired Federated Learning for OOD Generalization
Jiayuan Zhang, Xuefeng Liu, Jianwei Niu et al.
Causality Meets the Table: Debiasing LLMs for Faithful TableQA via Front-Door Intervention
Zhen Yang, Ziwei Du, Minghan Zhang et al.
Causal LLM Routing: End-to-End Regret Minimization from Observational Data
Asterios Tsiourvas, Wei Sun, Georgia Perakis
Causal Logistic Bandits with Counterfactual Fairness Constraints
Jiajun Chen, Jin Tian, Chris Quinn
Causally Motivated Sycophancy Mitigation for Large Language Models
Haoxi Li, Xueyang Tang, Jie ZHANG et al.
Causally Reliable Concept Bottleneck Models
Giovanni De Felice, Arianna Casanova Flores, Francesco De Santis et al.
Causal Mixture Models: Characterization and Discovery
Sarah Mameche, Janis Kalofolias, Jilles Vreeken
Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference
Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar et al.
Causal-PIK: Causality-based Physical Reasoning with a Physics-Informed Kernel
Carlota Parés Morlans, Michelle Yi, Claire Chen et al.
Causal-R: A Causal-Reasoning Geometry Problem Solver for Optimized Solution Exploration
Wenjun Wu, Lingling Zhang, Bo Zhao et al.
Causal Reasoning and Large Language Models: Opening a New Frontier for Causality
Chenhao Tan, Robert Ness, Amit Sharma et al.
Causal Representation Learning from Multimodal Biomedical Observations
Yuewen Sun, Lingjing Kong, Guangyi Chen et al.
Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning
Xiangning Yu, Zhuohan Wang, Linyi Yang et al.