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Paper Citation Record · LEDGER

Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2312.11420.

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

pith.paper-citation-record.v1
2312.11420 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 2026-08-11T06:34:44.6726+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:06:27.592753Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T15:21:44.731490Z

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 5feda48b-779a-4267-9769-14851f98127f · inbound

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 166

Resolution
verified exact
arxiv_id, observed 2026-05-13T11:32:36.873198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-13T11:32:36.738536Z digest=sha256:c942a63162289155b0316c8325fe28f794a800d31113ba7c8a0cd64611f23ef8

Observation e2b91644-fa16-4c52-9e52-76cd9cb8ce8c · inbound

$\texttt{BATCLIP}$: Bimodal Online Test-Time Adaptation for CLIP cites this paper.

$\texttt{BATCLIP}$: Bimodal Online Test-Time Adaptation for CLIP Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-11T23:06:27.592753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:06:27.592753Z digest=sha256:0aa99b3660fa67c8bb53c0d260e0e39aa7677b6bd489f6c766a0f46eb1840e9d

Observation ef8a27a6-b273-4cdf-9028-93c0aa01e148 · inbound

Parameter-Efficient Fine-Tuning for Foundation Models cites this paper.

Parameter-Efficient Fine-Tuning for Foundation Models Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-10T15:38:03.085413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:38:03.085413Z digest=sha256:f9d990023acbf2ef1f52abbef12b8e71b8bc055b3cc91c80b271c56d130f878a

Observation b9c2548a-1bd4-4591-bade-9f5a0df76430 · inbound

Concept Drift Guided LayerNorm Tuning for Efficient Multimodal Metaphor Identification cites this paper.

Concept Drift Guided LayerNorm Tuning for Efficient Multimodal Metaphor Identification Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-22T15:21:44.734777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-22T15:19:38.717420Z digest=sha256:94a311e1515f4067d6d665030918cec830024b0366e3c804ee82076d72ac3ba9

Observation 4a33112b-6bd4-4033-a091-ec1427ed36c9 · inbound

Time Series Foundation Models for Multivariate Financial Time Series Forecasting cites this paper.

Time Series Foundation Models for Multivariate Financial Time Series Forecasting Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-06T18:49:26.576798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:49:26.576798Z digest=sha256:f35c02ac337044594ea6de359478b63b5170e711302b2eef682ef32779d9b908

Observation 0f0b55f4-82b3-490c-8f5a-67266f026894 · inbound

Implementing Adaptations for Vision AutoRegressive Model cites this paper.

Implementing Adaptations for Vision AutoRegressive Model Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T17:12:35.096296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:12:35.096296Z digest=sha256:b6dc3758c7f4f2f9dfb20e693a67aa1aa25298a77dd50aef11ddcf1e58250d33

Observation ae76d5cd-8e71-437a-abfa-5da13c3106dc · inbound

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification cites this paper.

Exploiting Layer Normalization Fine-tuning in Visual Transformer Foundation Models for Classification Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-05T22:05:31.286262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:05:31.286262Z digest=sha256:3b5868e32abceda733263b0bb1b25c4f70e2cc9651976a5fc69f59498004098c

Observation ae0879ef-8a52-4c96-b84a-96fd4e54c2ca · inbound

CrossEarth-Gate: Fisher-Guided Adaptive Tuning Engine for Efficient Adaptation of Cross-Domain Remote Sensing Semantic Segmentation cites this paper.

CrossEarth-Gate: Fisher-Guided Adaptive Tuning Engine for Efficient Adaptation of Cross-Domain Remote Sensing Semantic Segmentation Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-03T20:20:35.855108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:20:35.855108Z digest=sha256:d20098ffbedba91250704efec08f53076adcac1496b590e8b3e0337a468b30f0

Observation 85c87951-1c27-4c23-a30a-974909a0c7dc · inbound

Robust Promptable Video Object Segmentation cites this paper.

Robust Promptable Video Object Segmentation Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:22:29.372361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-13T07:18:20.281383Z digest=sha256:32f2dabc4beda2934699f36d8f96c13eb7bc3338217c0bfbb1579d9e36de3c71