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Paper Citation Record · LEDGER

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery

As of 8 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2506.05673.

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

pith.paper-citation-record.v1
2506.05673 v3

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:18:37.662142Z

measured 17 of 17 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 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

17 of 17 outbound references displayed

  • verified exact1
  • verified fuzzy6
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f03ee53-d777-4b2e-bfb6-49045ffb22c4 · outbound

This paper cites A data-centric approach to improve performance of deep learning models.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery A data-centric approach to improve performance of deep learning models

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:18:39.724859Z

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.

source=arxiv_source observed=2026-08-07T10:18:35.423876Z digest=sha256:5c7d4fac7c006ee82e96e6661aef863541ba2758bd1a82f831dae88be75d9ccd

Observation 8b7178b2-9d58-45b0-a82c-8d412b68cb75 · outbound

This paper cites A fast quartet tree heuristic for hierarchical clustering.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery A fast quartet tree heuristic for hierarchical clustering

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:18:39.506276Z

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.

source=arxiv_source observed=2026-08-07T10:18:35.526868Z digest=sha256:6416c2b624bb06db16524ffb43ddb3e2fd7a02fd518cb4e9401c05ca63769f3a

Observation 5cadefde-479b-4ab9-853f-aa2e9aba7013 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Imagenet: A large-scale hierarchical image database

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T10:18:35.686673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:18:35.686673Z digest=sha256:5b36825bd102849aaad19afcc980d34ce98137e6b7d7ddf9ff8c3488e9b69139

Observation da611709-d1d7-4c29-a54f-325ed1f27b91 · outbound

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

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Lora: Low-rank adaptation of large language models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T10:18:35.823998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:18:35.823998Z digest=sha256:cb1537c511a7eda9b7d087d38fe63bf8e42971060e459882721aa30e9027621c

Observation 9e680dd6-36aa-4499-9c02-409083667f38 · outbound

This paper cites The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T10:18:35.991365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:18:35.991365Z digest=sha256:efefd47581a46b0f921d3a123040cd5289d1aee07d4cb9189f21029b718aec49

Observation cfaafdd7-bfa8-4bbc-96f2-2cbd92633aac · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T10:18:36.123475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:18:36.123475Z digest=sha256:678d57c7dc551e336282cc9e36570d93df49ea4201fbb04c1998b111f37e6df5

Observation bfd627e3-bb64-43e8-95c2-e0d6346290e2 · outbound

This paper cites Describe Anything: Detailed Localized Image and Video Captioning.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Describe Anything: Detailed Localized Image and Video Captioning

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T10:18:36.280131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:18:36.280131Z digest=sha256:3aa7635a029025a581fd329a15890a53e0ae04d718dfdb40225aef1e561a4eb5

Observation 82fd7aca-8b86-42ee-b52f-09403253589f · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Rouge: A package for automatic evaluation of summaries

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T10:18:36.414092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:18:36.414092Z digest=sha256:06e2cd9f8ffb8466ed6bda272132779e7610a23cc46ee62364744550522c3fea

Observation 44259e8b-3eb5-409d-8347-e69566c76331 · outbound

This paper cites Llava-onevision-qwen2-0.5b-ov.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Llava-onevision-qwen2-0.5b-ov

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:18:39.234108Z

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.

source=arxiv_source observed=2026-08-07T10:18:36.563733Z digest=sha256:630aebe5a24a1e72a59c0eb7b20d1d4417262de4d20c5c1b7154535cbe1525d0

Observation 99f472e0-6929-416d-9cea-c82cfbbda90c · outbound

This paper cites Peft: State-of-the-art parameter-efficient fine-tuning methods.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Peft: State-of-the-art parameter-efficient fine-tuning methods

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T10:18:36.727566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:18:36.727566Z digest=sha256:416d4d071d30267b671e0d2fad2603886f29064e1cff78dc94d9095a85d174e5

Observation 4ca5ab7d-a7e9-4ba2-ae6d-28c7eefe4f04 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Bleu: a method for automatic evaluation of machine translation

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T10:18:36.840120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:18:36.840120Z digest=sha256:dea83389d1cb16c2e08b07a85fcd658dd543b5953842811195ea65531a7dc572

Observation 4c79e0ea-1976-452b-9ef1-98ea2237b9aa · outbound

This paper cites Introducing LLaVA - NeXT , 2024.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Introducing LLaVA - NeXT , 2024

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:18:38.951774Z

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.

source=arxiv_source observed=2026-08-07T10:18:36.978102Z digest=sha256:275da517af17e49ad716f8bb0f69a9c4c03f89bcbafdba6e5e133887879360de

Observation 64e50ee3-1aeb-43e3-9895-df732f5d483a · outbound

This paper cites Normalized web distance and word similarity., 2010.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Normalized web distance and word similarity., 2010

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:18:38.579045Z

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.

source=arxiv_source observed=2026-08-07T10:18:37.036547Z digest=sha256:a70ec48a9e95a74b8395a692dbb291febd8d0de5253661c9b335e7b9367ee3d1

Observation ffcbe7bb-c07d-4208-86d2-fbd79bb61fec · outbound

This paper cites Efficient human-in-loop deep learning model training with iterative refinement and statistical result validation.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Efficient human-in-loop deep learning model training with iterative refinement and statistical result validation

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:18:37.994654Z

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.

source=arxiv_source observed=2026-08-07T10:18:37.185806Z digest=sha256:11768eb84cfa8364cbdcc9ba710fac6c0ada3715c50a6a59a871af684bda342c

Observation 2d90e9a8-6f36-4858-af4b-47171a740b24 · outbound

This paper cites Sigmoid loss for language image pre-training, 2023.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Sigmoid loss for language image pre-training, 2023

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T10:18:37.340210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:18:37.340210Z digest=sha256:37543c20c8f27f061599f9d3ee1e649e157bc042379851ce0b9df0bc31c0b099

Observation 96354771-7e19-4834-95c0-1b597c161c37 · outbound

This paper cites Long-clip: Unlocking the long-text capability of clip.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery Long-clip: Unlocking the long-text capability of clip

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:18:38.361823Z

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.

source=arxiv_source observed=2026-08-07T10:18:37.461997Z digest=sha256:f9fd9e848398c7717a173e0c4d78da8d3750d1ec195787dc5ccedf44b741af3b

Observation 1ed74d1e-8008-45f3-b0dd-8b8a594b1dd3 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery BERTScore: Evaluating Text Generation with BERT

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T10:18:37.662142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:18:37.662142Z digest=sha256:9c242b1b08175db13f310d45a75d4fa795f4568d351fb848c4b9d1ddccfee9e1

Pith citing papers

No inbound Pith citation observations are available.