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Paper Citation Record · LEDGER

Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty

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.

pith.paper-citation-record.v1
2308.02019 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:44:00.659142Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-22T14:06:38.082725Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8eb6c18a-5c4c-4d40-b3e7-89d8725f6d07 · inbound

Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security cites this paper.

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

Resolution
verified exact
arxiv_id, observed 2026-05-17T00:57:26.737571Z

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.

source=pdf_text observed=2026-05-17T00:57:26.303195Z digest=sha256:4fa585144e612de4b9c90dc0dcfdeb7771428b12cb6e53c5d0d62c81d0c22a56

Observation 8aec52a6-4426-4d97-88f8-17b905a716ff · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

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

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:39:33.549278Z

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.

source=pdf_text observed=2026-05-15T02:39:33.007894Z digest=sha256:bdedb6f4de31973e326316f2c84e8893f39af99f5c5dbe9df6f97ca604481aca

Observation 878a148a-0bcb-4fc8-86d7-4e755cb41522 · inbound

SHARP: Accelerating Language Model Inference by SHaring Adjacent layers with Recovery Parameters cites this paper.

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

Resolution
unresolved
no resolver link, observed 2026-08-08T13:44:00.659142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T13:44:00.659142Z digest=sha256:0dc34e2848d63ae55da9bd9f13e6102e9c28b5c5dbde22b18c48a8e6f72c24f1

Observation fae18880-b6dc-4a66-9424-60474cca7f56 · inbound

LLM-Powered AI Agent Systems and Their Applications in Industry cites this paper.

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

Resolution
verified exact
arxiv_id, observed 2026-05-22T14:06:38.085837Z

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.

source=pdf_text observed=2026-05-22T14:05:54.535411Z digest=sha256:341806f705c56df0ae4e6ad7ef6024a6eedd6eb4d7121becdbf7cc0c8b29e6e4

Observation 7e41aa38-ff46-4ba9-8ab9-2384f277e640 · inbound

Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation cites this paper.

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

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:13.520349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:13.520349Z digest=sha256:ba4715313a63e8f76edbf3e8ac45cfeb7233d9d13740ca589b0825bfb947841a

Observation 7ef4a804-9d0b-4784-8126-ff010bf97736 · inbound

SCOUT: Teaching Pre-trained Language Models to Enhance Reasoning via Flow Chain-of-Thought cites this paper.

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

Resolution
unresolved
no resolver link, observed 2026-08-07T12:39:01.792404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:39:01.792404Z digest=sha256:2e9c973586f704f8d394a71840bfb6acd5e5b1efbaac090d1d718fd8d487deac

Observation e8975f7d-f1f9-43a4-bbe4-5d7b3c9f2384 · inbound

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models cites this paper.

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

Resolution
unresolved
no resolver link, observed 2026-08-06T23:57:26.323704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:57:26.323704Z digest=sha256:b21e8a75c22df4b2753e3464f4bf651c1eacdc09d9e526f761ad4410d491e233

Observation 3648a555-298b-4291-a034-82a2532b8fa9 · inbound

Flipping Knowledge Distillation: Leveraging Small Models' Expertise to Enhance LLMs in Text Matching cites this paper.

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:29:09.101214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:29:09.101214Z digest=sha256:8afbf874df8457435479a22e9e2659ee842da70336ce20164805eebf7fd2b039