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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 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 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 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:58:26.494807Z

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-17T00:57:26.303195Z digest=sha256:5742ea9e7ef6fe8f21b38f91384f68d989dad08c67a6e6c530ab7f35b808a745

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-15T02:39:33.007894Z digest=sha256:2985ec08613bd6d0538e0d2191d102d5b893940e9972b7002b89bd459a222426

Observation aa796316-2208-4277-9d42-0e3e298eca63 · inbound

Explainable LLM-driven Multi-dimensional Distillation for E-Commerce Relevance Learning cites this paper.

Explainable LLM-driven Multi-dimensional Distillation for E-Commerce Relevance Learning 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 2026-08-12T16:58:26.494807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:58:26.494807Z digest=sha256:fe01c8f7674943da6286d3741a464a899bf9b81605ee6a27b97f4826b39303d3

Observation c5b46c31-8e84-4a93-a34b-d85d6371dd6b · inbound

AntLM: Bridging Causal and Masked Language Models cites this paper.

AntLM: Bridging Causal and Masked Language Models Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-11T22:40:35.263387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:40:35.263387Z digest=sha256:8e85a92a2cc9d56b75a9e40643fca315be5faadb57400d60e329a5557f0f1859

Observation 33e7d941-5bf0-4d90-878b-f8104a175128 · inbound

InfiFusion: A Unified Framework for Enhanced Cross-Model Reasoning via LLM Fusion cites this paper.

InfiFusion: A Unified Framework for Enhanced Cross-Model Reasoning via LLM Fusion Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T22:08:35.198680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:08:35.198680Z digest=sha256:cea0c43885d2111357bcf5d6f9343cd438f602ad357665e65883478791710eb7

Observation 9e34aa2c-5175-4468-b5a0-c474dde97254 · inbound

Accelerating Large Language Models through Partially Linear Feed-Forward Network cites this paper.

Accelerating Large Language Models through Partially Linear Feed-Forward Network Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T19:29:57.449262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:29:57.449262Z digest=sha256:07191c0b3fb024895a35e653c66ea5963986a11c0643bfd88f6248aa1443edca

Observation 410cc8e8-d9a4-4331-8be7-78bdbd64e95e · inbound

GREEN-CODE: Learning to Optimize Energy Efficiency in LLM-based Code Generation cites this paper.

GREEN-CODE: Learning to Optimize Energy Efficiency in LLM-based Code Generation Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T18:49:26.103613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:49:26.103613Z digest=sha256:3552664dd1d0399078b72ebc1f0f14b117b988832579aabab44c84a39e0b8b82

Observation 36c72ab1-e71d-4eb6-bc8e-591423f3ff14 · inbound

iServe: An Intent-based Serving System for LLMs cites this paper.

iServe: An Intent-based Serving System for LLMs Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty

Reference 108

Resolution
unresolved
no resolver link, observed 2026-08-10T21:37:14.490344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:37:14.490344Z digest=sha256:98b555c8a2faf224015f8d0edad740ffb78af8fdbe2aa54e917ba60ad3350500

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=sha256:5c7a36ae25829cee8cfbede5caa965d71f98a35516d25d6d3becd73f7cc3bb76

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-22T14:05:54.535411Z digest=sha256:70a41161e670e2d5e1e782bada3c0cc6ba7add8e4054bf7b8e10647e6467df18

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=sha256:84d4f0e1a575e4f23f25f79f9e0afedb9ea301d206d60c5d402aa2b76b34dd77

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=sha256:605a80994c3e5a1b5f3311f0d0ae651ccb97c649733b73cce7665cf02655dd1d

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=sha256:6fd600641066eb4f017870199cb43eb45cfa7b061e6315d029398a92a04be0d0

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:c27daea9c7ccf8a067de7c7579d45c7eaf18e5907e2b811cc8b6a76e85a98377