Paper Citation Record · LEDGER

Parameter-Efficient Fine-Tuning for Foundation Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2501.13787.

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

pith.paper-citation-record.v1
2501.13787 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:00:53.886161Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:08:21.872201Z

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 9a396661-7194-4d09-9c32-792aaac1e40c · inbound

Taming LLMs by Scaling Learning Rates with Gradient Grouping cites this paper.

Taming LLMs by Scaling Learning Rates with Gradient Grouping Parameter-Efficient Fine-Tuning for Foundation Models

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-07T11:57:29.248704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e3ee090-1121-44a6-b0cf-9f0cbe96aa8c · inbound

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning cites this paper.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Parameter-Efficient Fine-Tuning for Foundation Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T16:16:46.514544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46b5848c-e6bc-4b93-881b-7820885ffc18 · inbound

HiCoLoRA: Addressing Context-Prompt Misalignment via Hierarchical Collaborative LoRA for Zero-Shot DST cites this paper.

HiCoLoRA: Addressing Context-Prompt Misalignment via Hierarchical Collaborative LoRA for Zero-Shot DST Parameter-Efficient Fine-Tuning for Foundation Models

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:56:31.680791Z

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.

Observation d0efff84-806d-495e-ad2c-72787fef6466 · 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 Parameter-Efficient Fine-Tuning for Foundation Models

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-03T20:20:35.839594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81b68212-aafb-4c57-b2e6-aabc8fbf7ac9 · inbound

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

Vision Transformer Finetuning Benefits from Non-Smooth Components Parameter-Efficient Fine-Tuning for Foundation Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T03:48:09.573090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ead16b97-e24b-4886-99e8-399c4f0b41f7 · inbound

GoodVibe: Security-by-Vibe for LLM-Based Code Generation cites this paper.

GoodVibe: Security-by-Vibe for LLM-Based Code Generation Parameter-Efficient Fine-Tuning for Foundation Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T01:03:26.865933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3b1a6d7-e429-4172-8852-185057331110 · inbound

CURE:Circuit-Aware Unlearning for LLM-based Recommendation cites this paper.

CURE:Circuit-Aware Unlearning for LLM-based Recommendation Parameter-Efficient Fine-Tuning for Foundation Models

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-13T16:48:02.730668Z

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.

Observation 14c04486-e613-42f2-a790-521b38265021 · inbound

A Numerical PDEs Approach to Evolution Equations in Shape Analysis Based on Regularized Morphoelasticity cites this paper.

A Numerical PDEs Approach to Evolution Equations in Shape Analysis Based on Regularized Morphoelasticity Parameter-Efficient Fine-Tuning for Foundation Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-13T12:04:13.336341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7349027c-2850-4b01-a1e6-5efab70b8e2f · inbound

IntentVLM: Open-Vocabulary Intention Recognition through Forward-Inverse Modeling with Video-Language Models cites this paper.

IntentVLM: Open-Vocabulary Intention Recognition through Forward-Inverse Modeling with Video-Language Models Parameter-Efficient Fine-Tuning for Foundation Models

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:46:11.507164Z

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.

Observation b4f6faa0-72a5-4e88-acd3-547091e260f1 · inbound

The Hidden Power of Scaling Factor in LoRA Optimization cites this paper.

The Hidden Power of Scaling Factor in LoRA Optimization Parameter-Efficient Fine-Tuning for Foundation Models

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T14:08:21.873900Z

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.

Observation fe3a21cf-1a1e-41c2-8f91-06e1b6e4b13d · inbound

Energy- and Memory-Efficient PEFT Methods for Personalized On-Device SLMs on Consumer GPUs cites this paper.

Energy- and Memory-Efficient PEFT Methods for Personalized On-Device SLMs on Consumer GPUs Parameter-Efficient Fine-Tuning for Foundation Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T23:25:09.452833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e78e1bd-31f6-49a7-b596-52f600ce70dc · inbound

APQF: Agentic Profiling-Guided Structured Pruning and Mixed-Precision Quantization with Adaptive Fine-Tuning cites this paper.

APQF: Agentic Profiling-Guided Structured Pruning and Mixed-Precision Quantization with Adaptive Fine-Tuning Parameter-Efficient Fine-Tuning for Foundation Models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-08T12:00:53.886161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.