arXiv (All)
open access
Personalized Task Dependency Graphs for Mitigating Signal Erosion in Multi-Task Recommendation
Optimizing multiple conversion objectives is a core challenge in industrial recommendation, often limited by signal erosion in rigid architectures. Existing Multi-Task Learning (MTL) methods typically enforce uniform dependency strengths across a static conversion funnel, overlooking how task correl
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
- TRIPROBE: Probing Task Separability Beyond Classification for XAI#1012706
- TRIPROBE: Probing Task Separability Beyond Classification for XAI#965470
- A TEMPORALLY AWARE, CROSS-MODAL MULTI-TASK FRAMEWORK FOR JOINT PREDICTION OF PHQ-9, GAD-7, AND UCLA SCALE FROM DUAL-STREAM BEHAVIORAL DATA#413188
- Speech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalization#173253
- Selection-Aware Stress Testing for Interactive Agents#818950
Record · ID 971525
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