A Unified Approach to Interpreting Knowledge Distillation for Large Language Models via Interactions
arXiv 2607.08776•3ff1692c132a4607ddeb861c875414d62053b8ce27150c1bc23aa00f92890752
CIPDaDaDa_dataset','dataset_release','GPU_inference','sparse_inferDirectorHEROLLMLieBNMoERiemannian_normalizationStickyMoEbatch_normalizationdata_pricingexpert_placementfederated_continual_learningfew-bitflow_matchinginteraction_decompositionknowledge_distillationmixture_of_expertsmodel_compressionmolecular_generationoptimal_transportquantizationroutingserving_systemssigned_symmetric_quantization
Paper metadata
- arXiv ID
- 2607.08776
- Version
- Not specified by this published record
- Category
- Computer Science — Machine Learning (cs.LG)
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Evidence and limitations
- Source ID
- arxiv_cs_lg
- Record identifier
- 3ff1692c132a4607ddeb861c875414d62053b8ce27150c1bc23aa00f92890752
- Enrichment time
- 2026-07-13T08:52:22Z
- AI-assisted enrichment
- Yes
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