Paper Citation Record · LEDGER

What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1911.03090.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1911.03090 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:22:20.543117Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:38:44.327675Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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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 4e5bda04-9ed4-4bdb-a057-09ae1b3682f0 · inbound

DiffoRA: Enabling Parameter-Efficient Fine-Tuning via Differential Module Selection cites this paper.

DiffoRA: Enabling Parameter-Efficient Fine-Tuning via Differential Module Selection What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T23:22:20.543117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 064d4aa9-d317-4589-b4d0-5b971637e53a · inbound

Task-agnostic Low-rank Residual Adaptation for Efficient Federated Continual Fine-Tuning cites this paper.

Task-agnostic Low-rank Residual Adaptation for Efficient Federated Continual Fine-Tuning What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:54:52.974868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1e095396-bfff-4435-96cc-6e05062d2135 · inbound

On Finetuning Tabular Foundation Models cites this paper.

On Finetuning Tabular Foundation Models What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T05:01:16.092844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8156c2eb-62bd-4796-9ebe-ca1460e7ab41 · inbound

Tiny Reward Models cites this paper.

Tiny Reward Models What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:07.144511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2384074e-1fc6-4345-bf64-4ff67428de20 · inbound

MoEcho: Exploiting Side-Channel Attacks to Compromise User Privacy in Mixture-of-Experts LLMs cites this paper.

MoEcho: Exploiting Side-Channel Attacks to Compromise User Privacy in Mixture-of-Experts LLMs What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T18:11:08.573875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14656aaa-7b07-4b07-8e06-1a61be28fcde · inbound

Vision Transformer Finetuning Benefits from Non-Smooth Components cites this paper.

Vision Transformer Finetuning Benefits from Non-Smooth Components What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T03:48:09.552919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88f3bf81-28e8-476f-a4bb-6f66af25a16b · inbound

BID-LoRA: A Parameter-Efficient Framework for Continual Learning and Unlearning cites this paper.

BID-LoRA: A Parameter-Efficient Framework for Continual Learning and Unlearning What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:11:02.712170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 50683aa4-52c1-4cb4-b85b-61c4fb0013ac · inbound

A Causal Language Modeling Detour Improves Encoder Continued Pretraining cites this paper.

A Causal Language Modeling Detour Improves Encoder Continued Pretraining What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-13T04:37:15.692380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a031fde4-a379-4787-a030-7794dad692fd · inbound

Landsat-Sentinel-2 Algal Bloom Mapping Using Vision Transformers: Model Description, Implementation, and Examples cites this paper.

Landsat-Sentinel-2 Algal Bloom Mapping Using Vision Transformers: Model Description, Implementation, and Examples What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:38:44.329052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.