arXiv (All)
open access
RAPID: Reliability-Aware Pair Importance Distillation
Inter example relational distillation transfers a teacher's representation geometry by matching relations among examples within a mini batch. Computing all pairs has quadratic complexity in the batch size, whereas uniform subsampling may use a limited relation budget inefficiently. We introduce Reli
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
- Relational Representation Distillation#820149
- PSM: Dataset Distillation Based on Precise Statistical Matching by Difficulty#1119372
- Optimizing Teacher-Student Partitioning for Scalable Knowledge Distillation on HPC Systems#319646
- Distill What You Trust: Reliability-Aware Multi-Teacher On-Policy Distillation#1049433
- Triangle Criterion: a mixed-state magic criterion with applications in distillation and detection#1062823
Record · ID 972543
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