Paper Citation Record · LEDGER

Reimagining Parameter Space Exploration with Diffusion Models

As of 20 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2506.17807.

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

pith.paper-citation-record.v1
2506.17807 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:06:15.291559Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

verified exact1
verified fuzzy8
unresolved11
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 558319a6-ee28-44cc-b744-f78e35b99829 · outbound

This paper cites Learning deep architectures for ai.

Reimagining Parameter Space Exploration with Diffusion Models Learning deep architectures for ai

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:06:15.598419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0ee44c0a-67c5-49d8-ae27-6da264b0c87b · outbound

This paper cites SMASH: One-Shot Model Architecture Search through HyperNetworks.

Reimagining Parameter Space Exploration with Diffusion Models SMASH: One-Shot Model Architecture Search through HyperNetworks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.212549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd3c191b-e044-4dd8-8fa4-e809655e48d9 · outbound

This paper cites Z-score normalization, hubness, and few-shot learning.

Reimagining Parameter Space Exploration with Diffusion Models Z-score normalization, hubness, and few-shot learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:06:15.587356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 02c9c5a7-ff15-49a2-83b5-6db83e2e9312 · outbound

This paper cites HyperNetworks.

Reimagining Parameter Space Exploration with Diffusion Models HyperNetworks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.220688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dec3302c-33c6-4cd0-b14d-fd4ba3c9451c · outbound

This paper cites The impact of initialization on lora finetuning dynamics.

Reimagining Parameter Space Exploration with Diffusion Models The impact of initialization on lora finetuning dynamics

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:06:15.576560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 95d817ee-1e80-46ce-8fa0-977b6c6a0ed5 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Reimagining Parameter Space Exploration with Diffusion Models Lora: Low-rank adaptation of large language models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:06:15.564753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ae555ae1-45ee-4f32-8678-975357409886 · outbound

This paper cites K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning.

Reimagining Parameter Space Exploration with Diffusion Models K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.236825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 755b00a1-5973-4986-b1c2-c28ff3aae7c7 · outbound

This paper cites Learning to Learn with Generative Models of Neural Network Checkpoints.

Reimagining Parameter Space Exploration with Diffusion Models Learning to Learn with Generative Models of Neural Network Checkpoints

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.241149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aba8967c-a01b-4fce-9c47-de3a80410f8f · outbound

This paper cites In-situ fine-tuning of wildlife models in iot-enabled camera traps for efficient adaptation.

Reimagining Parameter Space Exploration with Diffusion Models In-situ fine-tuning of wildlife models in iot-enabled camera traps for efficient adaptation

Reference 9

Resolution: verified exact; raw_fallback, observed 2026-08-15T19:06:15.411812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a034b5ae-2c35-4b4e-bf32-0b0829944f01 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Reimagining Parameter Space Exploration with Diffusion Models High-resolution image synthesis with latent diffusion models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.248694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59cc6cec-82e9-49a5-8be3-6fd5a9e53d13 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Reimagining Parameter Space Exploration with Diffusion Models U-net: Convolutional networks for biomedical image segmentation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.253161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7763a0a0-6487-4b8c-baaa-2d6449e666eb · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

Reimagining Parameter Space Exploration with Diffusion Models Deep unsupervised learning using nonequilibrium thermodynamics

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.256798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d0a7786-22ef-4c93-8eb5-71b060e3a0b3 · outbound

This paper cites Denoising Diffusion Implicit Models.

Reimagining Parameter Space Exploration with Diffusion Models Denoising Diffusion Implicit Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.260651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a1b9972-490e-464d-9f50-4411e9ea0396 · outbound

This paper cites Diffusion-based neural network weights generation.

Reimagining Parameter Space Exploration with Diffusion Models Diffusion-based neural network weights generation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:06:15.533110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 94b59f4c-81af-4bc6-815e-94e02aca7fb0 · outbound

This paper cites Snapshot serengeti, high-frequency annotated camera trap images of 40 mammalian species in an african savanna.

Reimagining Parameter Space Exploration with Diffusion Models Snapshot serengeti, high-frequency annotated camera trap images of 40 mammalian species in an african savanna

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:06:15.521430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3cb50dc6-ca85-44e2-b7c3-13f6f7da4dac · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks.

Reimagining Parameter Space Exploration with Diffusion Models Efficientnet: Rethinking model scaling for convolutional neural networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.272015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3529569d-6d98-4d2a-a083-4f6a0a777e86 · outbound

This paper cites Attention is all you need.

Reimagining Parameter Space Exploration with Diffusion Models Attention is all you need

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.275622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation babf6da7-fdf4-4f2d-8867-5b0080afda67 · outbound

This paper cites Neural Network Diffusion.

Reimagining Parameter Space Exploration with Diffusion Models Neural Network Diffusion

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:15.279310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40bc1349-5da5-4cf9-a141-79a31488db6c · outbound

This paper cites Sindiffusion: Learning a diffusion model from a single natural image.

Reimagining Parameter Space Exploration with Diffusion Models Sindiffusion: Learning a diffusion model from a single natural image

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:06:15.494958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 310740a4-e4ce-405f-a23d-eecf4a732f6e · outbound

This paper cites Model soups: aver- aging weights of multiple fine-tuned models improves accuracy without increasing inference time.

Reimagining Parameter Space Exploration with Diffusion Models Model soups: aver- aging weights of multiple fine-tuned models improves accuracy without increasing inference time

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:06:15.482885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 246391e6-cd6f-4a3b-8712-4d8f31b4940d · outbound

This paper cites (5) In this way, DDIM could deterministically recover the same imagex0 from the specified noisexT.

Reimagining Parameter Space Exploration with Diffusion Models (5) In this way, DDIM could deterministically recover the same imagex0 from the specified noisexT

Reference 21

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T19:06:15.470938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.