synthetic data
Data generated artificially using algorithms rather than collected from real-world events, often used to augment training datasets or create privacy-preserving data for training purposes.
- 3D-Prover: Diversity Driven Theorem Proving With Determinantal Point Processes
- A Closer Look at Model Collapse: From a Generalization-to-Memorization Perspective
- A solvable model of learning generative diffusion: theory and insights
- APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay
- Adaptive Prediction-Powered AutoEval with Reliability and Efficiency Guarantees
- Advancing Wasserstein Convergence Analysis of Score-Based Models: Insights from Discretization and Second-Order Acceleration
- COME: Adding Scene-Centric Forecasting Control to Occupancy World Model
- Causal Mixture Models: Characterization and Discovery
- ConTextTab: A Semantics-Aware Tabular In-Context Learner
- Constrained Posterior Sampling: Time Series Generation with Hard Constraints
- Coupling Generative Modeling and an Autoencoder with the Causal Bridge
- Dataset Distillation for Pre-Trained Self-Supervised Vision Models
- Differentiable Cyclic Causal Discovery Under Unmeasured Confounders
- Diffusing DeBias: Synthetic Bias Amplification for Model Debiasing
- Effortless, Simulation-Efficient Bayesian Inference using Tabular Foundation Models
- Escaping Collapse: The Strength of Weak Data for Large Language Model Training
- Estimating Hitting Times Locally at Scale
- Estimation of Treatment Effects in Extreme and Unobserved Data
- First SFT, Second RL, Third UPT: Continual Improving Multi-Modal LLM Reasoning via Unsupervised Post-Training
- Flick: Empowering Federated Learning with Commonsense Knowledge
- From Flat to Hierarchical: Extracting Sparse Representations with Matching Pursuit
- From stability of Langevin diffusion to convergence of proximal MCMC for non-log-concave sampling
- GRIP: A Graph-Based Reasoning Instruction Producer
- Gene Regulatory Network Inference in the Presence of Selection Bias and Latent Confounders
- Generalized Top-k Mallows Model for Ranked Choices
- Implicit Generative Property Enhancer
- Improving the Generation and Evaluation of Synthetic Data for Downstream Medical Causal Inference
- Inpainting the Neural Picture: Inferring Unrecorded Brain Area Dynamics from Multi-Animal Datasets
- Learning-Augmented Online Bipartite Fractional Matching
- Leveraging robust optimization for llm alignment under distribution shifts
- NOBLE - Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models
- Network two-sample test for block models
- On the Edge of Memorization in Diffusion Models
- Optimal Neural Compressors for the Rate-Distortion-Perception Tradeoff
- Optimal Online Change Detection via Random Fourier Features
- PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding
- Practical Kernel Selection for Kernel-based Conditional Independence Test
- Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning
- Provable Meta-Learning with Low-Rank Adaptations
- RLGF: Reinforcement Learning with Geometric Feedback for Autonomous Driving Video Generation
- Rectifying Soft-Label Entangled Bias in Long-Tailed Dataset Distillation
- SAO-Instruct: Free-form Audio Editing using Natural Language Instructions
- SCAN: Self-Denoising Monte Carlo Annotation for Robust Process Reward Learning
- SNEAKDOOR: Stealthy Backdoor Attacks against Distribution Matching-based Dataset Condensation
- SPMDM: Enhancing Masked Diffusion Models through Simplifing Sampling Path
- SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning
- Sample-Efficient Multi-Round Generative Data Augmentation for Long-Tail Instance Segmentation
- Self-Supervised Discovery of Neural Circuits in Spatially Patterned Neural Responses with Graph Neural Networks
- Self-Verification Provably Prevents Model Collapse in Recursive Synthetic Training
- Spend Wisely: Maximizing Post-Training Gains in Iterative Synthetic Data Bootstrapping
- Structural Entropy Guided Agent for Detecting and Repairing Knowledge Deficiencies in LLMs
- Sum Estimation under Personalized Local Differential Privacy
- Synthetic-powered predictive inference
- T-REGS: Minimum Spanning Tree Regularization for Self-Supervised Learning
- The Flood Complex: Large-Scale Persistent Homology on Millions of Points
- This Time is Different: An Observability Perspective on Time Series Foundation Models
- Towards Self-Refinement of Vision-Language Models with Triangular Consistency
- Towards Syn-to-Real IQA: A Novel Perspective on Reshaping Synthetic Data Distributions
- Transductive Conformal Inference for Full Ranking
- Universal Sequence Preconditioning
- Virus Infection Attack on LLMs: Your Poisoning Can Spread "VIA" Synthetic Data
- When Additive Noise Meets Unobserved Mediators: Bivariate Denoising Diffusion for Causal Discovery
- When Models Don’t Collapse: On the Consistency of Iterative MLE