Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2308.02019.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T13:44:00.659142Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T14:06:38.082725Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 8eb6c18a-5c4c-4d40-b3e7-89d8725f6d07 · inbound
Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty
Reference 256
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8aec52a6-4426-4d97-88f8-17b905a716ff · inbound
A Survey on Efficient Inference for Large Language Models Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty
Reference 134
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 878a148a-0bcb-4fc8-86d7-4e755cb41522 · inbound
SHARP: Accelerating Language Model Inference by SHaring Adjacent layers with Recovery Parameters Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty
Reference 80
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fae18880-b6dc-4a66-9424-60474cca7f56 · inbound
LLM-Powered AI Agent Systems and Their Applications in Industry Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty
Reference 89
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7e41aa38-ff46-4ba9-8ab9-2384f277e640 · inbound
Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty
Reference 44
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7ef4a804-9d0b-4784-8126-ff010bf97736 · inbound
SCOUT: Teaching Pre-trained Language Models to Enhance Reasoning via Flow Chain-of-Thought Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty
Reference 32
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e8975f7d-f1f9-43a4-bbe4-5d7b3c9f2384 · inbound
GenRecal: Generation after Recalibration from Large to Small Vision-Language Models Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty
Reference 97
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3648a555-298b-4291-a034-82a2532b8fa9 · inbound
Flipping Knowledge Distillation: Leveraging Small Models' Expertise to Enhance LLMs in Text Matching Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty
Reference 30
Source-reported events for the cited work
Unavailable: canonical work link unavailable.