Demystifying Low-Rank Knowledge Distillation in Large Language Models: Convergence, Generalization, and Information-Theoretic Guarantees
arXiv 2603.22355•23eee20b23360419b36222c2619442204501db40e2ce85005d703d2b2bc29927
Bayesian-inferenceLaplace-approximationPAC-BayesRLHFRashomon-setSPDEactive-learningconvergencedeep-learningdifferential-privacye-valuesgeneralizationinformation-theoryinterpretabilityknowledge-distillationlarge-language-modelslow-rankmachine-learningmodel-evaluationpost-selectionposterior-contractionprivacytheoryvariational-inferencevine-copulas
Paper metadata
- arXiv ID
- 2603.22355
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
The PDF link points to arxiv.org. Baitaphish does not expose a private stored PDF.
Evidence and limitations
- Source ID
- arxiv_stat_ml
- Record identifier
- 23eee20b23360419b36222c2619442204501db40e2ce85005d703d2b2bc29927
- Enrichment time
- 2026-03-25T07:23:54Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.