data distribution

When Pretty Isn't Useful: Investigating Why Modern Text-to-Image Models Fail as Reliable Training Data Generators CVPR 2026 Provable Efficiency of Guidance in Diffusion Models for General Data Distribution ICML 2025 SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization ICLR 2025 Analyzing Diffusion Models on Synthesizing Training Datasets ACML 2024 Benchmark Transparency: Measuring the Impact of Data on Evaluation NAACL 2024 BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization ICML 2024 Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them) ICML 2024 DEM: Distribution Edited Model for Training with Mixed Data Distributions EMNLP 2024 Dissect Black Box: Interpreting for Rule-Based Explanations in Unsupervised Anomaly Detection NeurIPS 2024 OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning NeurIPS 2024 Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation NeurIPS 2024 Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness NeurIPS 2023 Analyzing Diffusion as Serial Reproduction ICML 2023 Deconstructing Distributions: A Pointwise Framework of Learning ICLR 2023 Learned Index with Dynamic ε ICLR 2023 On Distribution Dependent Sub-Logarithmic Query Time of Learned Indexing ICML 2023 What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement. NeurIPS 2023 DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation AAAI 2022 Generalized Data Distribution Iteration ICML 2022 How to Learn when Data Gradually Reacts to Your Model AISTATS 2022 Rethinking Adversarial Transferability from a Data Distribution Perspective ICLR 2022 Towards Bridging Sample Complexity and Model Capacity AAAI 2022 Estimating High Order Gradients of the Data Distribution by Denoising NeurIPS 2021 How to Learn when Data Reacts to Your Model: Performative Gradient Descent ICML 2021 Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks NeurIPS 2021