Paper Citation Record · LEDGER

Products-10K: A Large-scale Product Recognition Dataset

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2008.10545.

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

pith.paper-citation-record.v1
2008.10545 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 2026-08-19T06:32:44.657259+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:32:24.201044Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:19:13.591991Z

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 4e8b4c5c-56ae-4a3a-b07d-d695b55c2e2e · inbound

Enhancing Fine-Grained Vision-Language Pretraining with Negative Augmented Samples cites this paper.

Enhancing Fine-Grained Vision-Language Pretraining with Negative Augmented Samples Products-10K: A Large-scale Product Recognition Dataset

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T16:32:24.201044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 397b87bc-b8c0-4119-8483-e941bd38663e · inbound

Enhancing Cost Efficiency in Active Learning with Candidate Set Query cites this paper.

Enhancing Cost Efficiency in Active Learning with Candidate Set Query Products-10K: A Large-scale Product Recognition Dataset

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T16:28:25.794042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f796522b-5563-49b7-bc04-27ec0fc6311a · inbound

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation cites this paper.

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation Products-10K: A Large-scale Product Recognition Dataset

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-22T18:26:55.277570Z

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 65d4a3f4-3297-4456-872d-f15d513a855e · inbound

PictSure: Pretraining Embeddings Matters for In-Context Learning Image Classifiers cites this paper.

PictSure: Pretraining Embeddings Matters for In-Context Learning Image Classifiers Products-10K: A Large-scale Product Recognition Dataset

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T00:39:55.759249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0ad4be2-2bd7-4f7b-a3f4-addacd6dfd6d · inbound

SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights cites this paper.

SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Products-10K: A Large-scale Product Recognition Dataset

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:23.364096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64c81812-9400-4538-a081-5b274703b06d · inbound

How far have we gone in Generative Image Restoration? A study on its capability, limitations and evaluation practices cites this paper.

How far have we gone in Generative Image Restoration? A study on its capability, limitations and evaluation practices Products-10K: A Large-scale Product Recognition Dataset

Reference 108

Resolution: unresolved; no resolver link, observed 2026-07-15T14:53:30.608642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c45925e-0924-4d46-a843-7d465f5cffcc · inbound

Beyond Semantic Search: Towards Referential Anchoring in Composed Image Retrieval cites this paper.

Beyond Semantic Search: Towards Referential Anchoring in Composed Image Retrieval Products-10K: A Large-scale Product Recognition Dataset

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:35:50.555871Z

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 c0195955-6ef1-483e-aee6-832354f69ec3 · inbound

FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition cites this paper.

FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition Products-10K: A Large-scale Product Recognition Dataset

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:42:58.653828Z

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 47c2034f-f294-4f34-9bf8-ea2786985ca9 · inbound

FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition cites this paper.

FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition Products-10K: A Large-scale Product Recognition Dataset

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:03:47.195992Z

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 de9efc01-9192-4da0-abcc-15600e2d31ac · inbound

What Matters for Grocery Product Retrieval with Open Source Vision Language Models cites this paper.

What Matters for Grocery Product Retrieval with Open Source Vision Language Models Products-10K: A Large-scale Product Recognition Dataset

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T12:03:15.414851Z

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 8b83bb29-460f-4a36-8742-ce3b5d4027cd · inbound

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: From Evaluation to Diagnosis cites this paper.

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: From Evaluation to Diagnosis Products-10K: A Large-scale Product Recognition Dataset

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-07-03T23:59:06.691950Z

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 0fabc851-cca2-48a8-b90f-21f1f068dad9 · inbound

ProductConsistency: Improving Product Identity Preservation in Instruction-Based Image Editing via SFT and RL cites this paper.

ProductConsistency: Improving Product Identity Preservation in Instruction-Based Image Editing via SFT and RL Products-10K: A Large-scale Product Recognition Dataset

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:19:13.593688Z

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.