Paper Citation Record · LEDGER

Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 30 inbound Pith citation observations for arXiv:2012.13255.

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

pith.paper-citation-record.v1
2012.13255 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 30 of 30 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:43:36.387826Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T11:09:46.577050Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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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 9ebd430f-e568-428e-a6e8-af8a5cfddb96 · inbound

Prefix-Tuning: Optimizing Continuous Prompts for Generation cites this paper.

Prefix-Tuning: Optimizing Continuous Prompts for Generation Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:57:25.130831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 09f407dd-8bc8-4250-ade5-b1a3f63ac589 · inbound

LoRA: Low-Rank Adaptation of Large Language Models cites this paper.

LoRA: Low-Rank Adaptation of Large Language Models Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-09T05:01:40.870617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4ae294c0-dbf4-4331-a97d-36fcee26a0fe · inbound

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

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-13T11:32:36.949559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f86e1917-3d17-4b67-93a3-1b6b18f82a8d · inbound

Small Language Models (SLMs) Can Still Pack a Punch: A survey (updated 2026) cites this paper.

Small Language Models (SLMs) Can Still Pack a Punch: A survey (updated 2026) Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-23T05:52:37.538773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 54d53c3d-4ecc-4400-83dd-217b2b2a99e4 · inbound

Document Retrieval Augmented Fine-Tuning (DRAFT) for safety-critical software assessments cites this paper.

Document Retrieval Augmented Fine-Tuning (DRAFT) for safety-critical software assessments Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-22T17:11:49.715631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5658877c-8b24-4641-be9b-f57e8843d9f6 · inbound

Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights cites this paper.

Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:01:46.053959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 56e2f820-1ebf-457c-ac67-2d2552239c7d · inbound

Little by Little: Continual Learning via Incremental Mixture of Rank-1 Associative Memory Experts cites this paper.

Little by Little: Continual Learning via Incremental Mixture of Rank-1 Associative Memory Experts Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:06:34.632662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 002c2b2a-b1d8-49b9-9e84-d8cc888a64fc · inbound

Sensitivity-LoRA: Low-Load Sensitivity-Based Fine-Tuning for Large Language Models cites this paper.

Sensitivity-LoRA: Low-Load Sensitivity-Based Fine-Tuning for Large Language Models Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-04T19:43:36.387826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bc12882-944b-4ae0-a888-95f331b2fb26 · inbound

HyperAdapt: Simple High-Rank Adaptation cites this paper.

HyperAdapt: Simple High-Rank Adaptation Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T13:46:25.877913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 45b4c998-8dc2-47fa-afcd-10502b6782c3 · inbound

CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure cites this paper.

CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:52:41.232875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8a167dd9-1f8e-435e-bfa9-174b65e0dede · inbound

Towards Understanding the Shape of Representations in Protein Language Models cites this paper.

Towards Understanding the Shape of Representations in Protein Language Models Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T13:54:18.668820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f016db4c-ba5d-4b3e-964d-5a53db5126e9 · inbound

The 3D Mirage: Probing and Taming 3D Hallucinations cites this paper.

The 3D Mirage: Probing and Taming 3D Hallucinations Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T15:53:51.075843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 665dab8a-29d2-481e-bcad-7deecdb057a0 · inbound

Training Transformers in Cosine Coefficient Space cites this paper.

Training Transformers in Cosine Coefficient Space Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:10:50.614560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ff19c483-7f68-4852-8a70-36294a079198 · inbound

ARIA: Adaptive Retrieval Intelligence Assistant -- A Multimodal RAG Framework for Domain-Specific Engineering Education cites this paper.

ARIA: Adaptive Retrieval Intelligence Assistant -- A Multimodal RAG Framework for Domain-Specific Engineering Education Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-16T07:52:32.993245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d75d2492-c916-4b1a-8a03-ba0c2360f08b · inbound

TLoRA: Task-aware Low Rank Adaptation of Large Language Models cites this paper.

TLoRA: Task-aware Low Rank Adaptation of Large Language Models Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 53

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T09:48:48.158531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3b4877fd-5944-4dfb-9b32-8ef277f7df81 · inbound

DP-FlogTinyLLM: Differentially private federated log anomaly detection using Tiny LLMs cites this paper.

DP-FlogTinyLLM: Differentially private federated log anomaly detection using Tiny LLMs Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 39

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T02:53:29.787076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b65a58da-bc9b-41ee-bc96-a9a425084f6f · inbound

UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors cites this paper.

UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 138

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:26:07.973751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation aab1b2b6-82cd-428d-b2f8-df0a0e6e27cf · inbound

DataDignity: Training Data Attribution for Large Language Models cites this paper.

DataDignity: Training Data Attribution for Large Language Models Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:26:10.346139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fd531250-db85-4c7b-b79b-c52b6954e381 · inbound

Emergent Symbolic Structure in Health Foundation Models: Extraction, Alignment, and Cross-Modal Transfer cites this paper.

Emergent Symbolic Structure in Health Foundation Models: Extraction, Alignment, and Cross-Modal Transfer Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 62

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T03:45:55.999225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f8d21098-b5aa-40f6-963f-0df9d9285249 · inbound

Combining pre-trained models via localized model averaging cites this paper.

Combining pre-trained models via localized model averaging Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 162

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T17:57:32.958945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ade2d6e1-3f8c-4ceb-96ee-3673f1bf50ba · inbound

LoCO: Low-rank Compositional Rotation Fine-tuning cites this paper.

LoCO: Low-rank Compositional Rotation Fine-tuning Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:53:42.612237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c618919c-8d8f-4d0e-bc9b-bf01b0096178 · inbound

Interpretable Discriminative Text Representations via Agreement and Label Disentanglement cites this paper.

Interpretable Discriminative Text Representations via Agreement and Label Disentanglement Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:49:41.172032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 51b84195-2dbd-4263-b5e7-0efc268326f9 · inbound

The Fine-Tuning Trap: Evaluating Negative Transfer and the Role of PEFT in Sub-1B Mathematical Reasoning cites this paper.

The Fine-Tuning Trap: Evaluating Negative Transfer and the Role of PEFT in Sub-1B Mathematical Reasoning Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:07:09.177227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b4226690-c68b-4daf-a2f8-b7792fc8f400 · inbound

Reversible Foundations: Training a 120B Sparse MoE through State-Preserving Scaling cites this paper.

Reversible Foundations: Training a 120B Sparse MoE through State-Preserving Scaling Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:07:09.428884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a486ae7c-c52b-4449-a8bc-d74d99a942f0 · inbound

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems cites this paper.

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 103

Resolution: verified exact; arxiv_id, observed 2026-07-04T11:09:46.578767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4bef54d0-6bfa-4883-91f2-d635b64cc5bc · inbound

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems cites this paper.

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-02T10:27:17.462186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7ca4583-d419-4370-ac31-038f60b9c54c · inbound

FRAME: Learning the Adaptation Domain with a Mixture of Fractional-Fourier Experts cites this paper.

FRAME: Learning the Adaptation Domain with a Mixture of Fractional-Fourier Experts Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T19:57:19.212262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d436607c-5239-4eea-ab53-6e46bd3c16ec · inbound

Co-Adaptive Multi-Task LoRA: Transfer-Aware, Label-Free Control of Domain Participation cites this paper.

Co-Adaptive Multi-Task LoRA: Transfer-Aware, Label-Free Control of Domain Participation Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 70

Resolution: unresolved; no resolver link, observed 2026-07-12T01:54:44.256835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3dd770c-182c-44ab-b863-463604ebb909 · inbound

SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling cites this paper.

SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 262

Resolution: unresolved; no resolver link, observed 2026-08-02T09:51:03.879892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b31f9d26-ec54-4dfe-8363-e3cea7a3fc57 · inbound

Emergent Sparsity in Frozen Random CNN Feature Extractors for Deep Reinforcement Learning cites this paper.

Emergent Sparsity in Frozen Random CNN Feature Extractors for Deep Reinforcement Learning Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T13:59:03.104886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.