arXiv (OAI Expanded)
open access
From Leakage to Fidelity: Reliable Benchmarking for Temporal Cascade Prediction
Temporal cascade prediction is widely studied, yet its empirical foundations remain fragile. Most existing works report results under random cascade splits that mix past and future signals, rely on datasets with limited features and no downstream conversion labels, and compare increasingly complex m
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- From Leakage to Fidelity: Reliable Benchmarking for Temporal Cascade Prediction#925071
- Detecting Spurious Periodic Generalization in Neural Networks (PGVP)#688606
- Real-Time Feature Engineering and Model Serving Architecture using Databricks Delta Live Tables. 9. 746-758. 10.32628#114553
- Multi-Modal Time Series Prediction via Mixture of Modulated Experts#1069735
- Fidel-TS: A High-Fidelity Multimodal Benchmark for Time Series Forecasting#1035319
Record · ID 920837
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive