Paper Citation Record · LEDGER

Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2401.17868.

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

pith.paper-citation-record.v1
2401.17868 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T00:49:55.206844Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

12
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 85449d0f-825a-4362-94c3-50ba742c4e74 · inbound

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization cites this paper.

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-23T22:28:31.063585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aecfe045-340b-480f-b08a-898d1b6cfd40 · inbound

Generalized SAM: Efficient Fine-Tuning of SAM for Variable Input Image Sizes cites this paper.

Generalized SAM: Efficient Fine-Tuning of SAM for Variable Input Image Sizes Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-05-23T21:28:27.544027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aac0b1b2-01a1-4fee-a5a9-540ef657f204 · inbound

Baltimore Atlas: FreqWeaver Adapter for Semi-supervised Ultra-high Spatial Resolution Land Cover Classification cites this paper.

Baltimore Atlas: FreqWeaver Adapter for Semi-supervised Ultra-high Spatial Resolution Land Cover Classification Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T23:59:15.489413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98ee29ae-a108-4f98-b86f-de20dfb07cb1 · inbound

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI cites this paper.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T21:54:09.686517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc78d84b-8380-405e-9b3c-4fe658d49651 · inbound

PHLoRA: data-free Post-hoc Low-Rank Adapter extraction from full-rank checkpoint cites this paper.

PHLoRA: data-free Post-hoc Low-Rank Adapter extraction from full-rank checkpoint Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T17:22:08.997472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccc915c8-cd69-426d-9175-e88c2c771754 · inbound

Dante: An Open Source Model Pre-Training and Fine-Tuning Tool for the Dafne Federated Framework for Medical Image Segmentation cites this paper.

Dante: An Open Source Model Pre-Training and Fine-Tuning Tool for the Dafne Federated Framework for Medical Image Segmentation Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-09T05:35:24.326616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 76a1b497-315e-4854-92ce-b291c412d3b2 · inbound

M$^4$-SAM: Multi-Modal Mixture-of-Experts with Memory-Augmented SAM for RGB-D Video Salient Object Detection cites this paper.

M$^4$-SAM: Multi-Modal Mixture-of-Experts with Memory-Augmented SAM for RGB-D Video Salient Object Detection Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:17:22.993461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0e8282d0-aa58-41d1-af78-98a66f16e2f5 · inbound

CLIP-Guided SAM: Parameter-Efficient Semantic Conditioning for Promptable Segmentation cites this paper.

CLIP-Guided SAM: Parameter-Efficient Semantic Conditioning for Promptable Segmentation Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T12:34:39.041561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b0e43c58-5457-4418-b266-53f9da76207c · inbound

Affordance2Action: Task-Conditioned Scene-level Affordance Grounding for Real-Time Manipulation cites this paper.

Affordance2Action: Task-Conditioned Scene-level Affordance Grounding for Real-Time Manipulation Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:46:32.444244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 626588e1-34d6-412e-b510-42d4a5be508f · inbound

CROSS: Cascaded Distillation and Dual-Constraint Grounding for Remote Sensing Referring Segmentation cites this paper.

CROSS: Cascaded Distillation and Dual-Constraint Grounding for Remote Sensing Referring Segmentation Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-06T00:48:47.023787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16f06ca4-2dc7-41b8-a8f7-4379986ac736 · inbound

CROSS: Cascaded Distillation and Dual-Constraint Grounding for Remote Sensing Referring Segmentation cites this paper.

CROSS: Cascaded Distillation and Dual-Constraint Grounding for Remote Sensing Referring Segmentation Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-08T00:49:55.206844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.