prediction accuracy
The ratio of correctly predicted outcomes to the total number of predictions made, serving as a direct measure of an AI model’s performance. It is often one of the primary metrics used for evaluating classification tasks.
- A Driving-Style-Adaptive Framework for Vehicle Trajectory Prediction
- A2Seek: Towards Reasoning-Centric Benchmark for Aerial Anomaly Understanding
- Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency
- Causal Spatio-Temporal Prediction: An Effective and Efficient Multi-Modal Approach
- Efficient Knowledge Transfer in Federated Recommendation for Joint Venture Ecosystem
- Hawk: Leveraging Spatial Context for Faster Autoregressive Text-to-Image Generation
- Homogeneous Algorithms Can Reduce Competition in Personalized Pricing
- Impartial Selection with Predictions
- Introducing FOReCAst: The Future Outcome Reasoning and Confidence Assessment Benchmark
- Kernel-based Equalized Odds: A Quantification of Accuracy-Fairness Trade-off in Fair Representation Learning
- Maximizing the Value of Predictions in Control: Accuracy Is Not Enough
- NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models
- Partial Physics Informed Diffusion Model for Ocean Chlorophyll Concentration Reconstruction
- Pre-trained Large Language Models Learn to Predict Hidden Markov Models In-context
- Procurement Auctions with Predictions: Improved Frugality for Facility Location
- RANK++LETR: Learn to Rank and Optimize Candidates for Line Segment Detection
- Reconciling Geospatial Prediction and Retrieval via Sparse Representations
- Remarkable Robustness of LLMs: Stages of Inference?
- SE-GUI: Enhancing Visual Grounding for GUI Agents via Self-Evolutionary Reinforcement Learning
- Towards Multiscale Graph-based Protein Learning with Geometric Secondary Structural Motifs