Deep Learning

Online Continuous Generalized Category Discovery ECCV 2024 Online Conversion Rate Prediction via Multi-Interval Screening and Synthesizing under Delayed Feedback AAAI 2024 Online GNN Evaluation Under Test-time Graph Distribution Shifts ICLR 2024 Online Posterior Sampling with a Diffusion Prior NeurIPS 2024 Online Relational Inference for Evolving Multi-agent Interacting Systems NeurIPS 2024 Online Stabilization of Spiking Neural Networks ICLR 2024 OnlineTAS: An Online Baseline for Temporal Action Segmentation NeurIPS 2024 On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey ACL 2024 Only Strict Saddles in the Energy Landscape of Predictive Coding Networks? NeurIPS 2024 On Manipulating Scene Text in the Wild With Diffusion Models WACV 2024 On Mechanistic Knowledge Localization in Text-to-Image Generative Models ICML 2024 On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability NeurIPS 2024 On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models NeurIPS 2024 On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes ICLR 2024 On provable privacy vulnerabilities of graph representations NeurIPS 2024 On Scaling Up a Multilingual Vision and Language Model CVPR 2024 On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs) NeurIPS 2024 On Stronger Computational Separations Between Multimodal and Unimodal Machine Learning ICML 2024 On task-relevant loss functions in meta-reinforcement learning L4DC 2024 On the Analysis of GAN-based Image-to-Image Translation with Gaussian Noise Injection ICLR 2024 On the Asymptotic Distribution of the Minimum Empirical Risk ICML 2024 On the Calibration of Human Pose Estimation ICML 2024 On the Comparison between Multi-modal and Single-modal Contrastive Learning NeurIPS 2024 On the Concept Trustworthiness in Concept Bottleneck Models AAAI 2024 On the connection between Noise-Contrastive Estimation and Contrastive Divergence AISTATS 2024