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Paper Citation Record · LEDGER

Fine-Grained Food Image Understanding via Target-Aware Data Alignment

As of 7 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2607.25794.

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

pith.paper-citation-record.v1
2607.25794 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T01:32:33.691163Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

22 of 22 outbound references displayed

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  • verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 71822307-3b9a-4fe5-9b57-976d2447c888 · outbound

This paper cites Large scale visual food recognition,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Large scale visual food recognition,

Reference 1

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Observation b909d30d-0a76-4638-bf09-67ba3619bf5c · outbound

This paper cites Food-101: Mining discriminative components with random forests,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Food-101: Mining discriminative components with random forests,

Reference 2

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doi, observed 2026-08-01T01:36:19.906506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3b0b58e3-1d0a-4c29-8752-b542e742649b · outbound

This paper cites Dishcovery Mission II Challenge: Where VLM meets food,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Dishcovery Mission II Challenge: Where VLM meets food,

Reference 3

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source=pdf_text observed=2026-08-01T01:32:31.018574Z digest=sha256:729d415dd89859ebc49192f42570e905b143e669b2d44612fd46c3287279762c

Observation 5011870a-4062-45ec-b15f-5a45f7943446 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Learning transferable visual models from natural language supervision,

Reference 4

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source=pdf_text observed=2026-08-01T01:32:31.096810Z digest=sha256:5ab9d3504d9adf1764b0e6ffb5826f4afa1a8acf44982166cc55127dff6232a2

Observation 1d4e9d48-164c-41fd-87cb-6cfa0f79bd8c · outbound

This paper cites Scaling up visual and vision-language representation learning with noisy text supervision,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Scaling up visual and vision-language representation learning with noisy text supervision,

Reference 5

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source=pdf_text observed=2026-08-01T01:32:31.209122Z digest=sha256:6bdcf8e6eb4941e979b0edacd73d3c0f8a68cf73f3fc5ddc09d7baee8868fe2a

Observation ec4cc4b1-1195-4617-88c6-7aede3e7e100 · outbound

This paper cites OpenCLIP,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment OpenCLIP,

Reference 6

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source=pdf_text observed=2026-08-01T01:32:31.316247Z digest=sha256:be4349e73a3f1b413de736a1727c4e64b02c34996c2c710ce9cfa028e33c012a

Observation 4bc8373a-9368-4d7a-9109-a9e0fb6563d3 · outbound

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

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Sigmoid loss for language image pre-training,

Reference 7

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Observation 2fb9aa6e-023d-45ea-9f50-5ea57f34cbfe · outbound

This paper cites Recipe1M+: A dataset for learning cross-modal embeddings for cooking recipes and food images,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Recipe1M+: A dataset for learning cross-modal embeddings for cooking recipes and food images,

Reference 8

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source=pdf_text observed=2026-08-01T01:32:31.524269Z digest=sha256:eb4de751c6806e8cc534524457d029904275aad47cbff8e0232adc28f8f20676

Observation 4113570c-a919-4009-8331-caa84c3b06da · outbound

This paper cites Passage Re-ranking with BERT.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Passage Re-ranking with BERT

Reference 9

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source=pdf_text observed=2026-08-01T01:32:31.632993Z digest=sha256:7837609148816039c0867b4f9ae9b199447ac4964d26746accef9fd31009ab31

Observation 50866322-c439-4de3-ac5b-987a2b194ab6 · outbound

This paper cites Reciprocal rank fusion outperforms Condorcet and individual rank learning methods,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Reciprocal rank fusion outperforms Condorcet and individual rank learning methods,

Reference 10

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source=pdf_text observed=2026-08-01T01:32:31.737098Z digest=sha256:ca14afdeecd4b758597d165b1ebf6143ff7ee8436162fbd3587eff48a4b45e31

Observation e08251a9-de2f-4b18-8d70-ade1ef08f85e · outbound

This paper cites Is ChatGPT good at search? Investigating large language models as re-ranking agents,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Is ChatGPT good at search? Investigating large language models as re-ranking agents,

Reference 11

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Observation ee499a87-f617-4c8f-965c-d14822c0ec41 · outbound

This paper cites CLIP-Adapter: Better vision-language models with feature adapters,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment CLIP-Adapter: Better vision-language models with feature adapters,

Reference 12

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source=pdf_text observed=2026-08-01T01:32:32.026185Z digest=sha256:633cd7cfa1aa1956b28ffddf54fe34ce7f3644d2fc6c4d1356c4be36355eca9e

Observation a0e35696-986c-463d-9c07-23fc58da0d66 · outbound

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

Fine-Grained Food Image Understanding via Target-Aware Data Alignment LoRA: Low-rank adaptation of large language models,

Reference 13

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source=pdf_text observed=2026-08-01T01:32:32.233068Z digest=sha256:6aa7d885bec8ce5c1ad666056fbcc5c9e442ca5d1e35b4b4325917788abee1f4

Observation c9e4422c-3f6b-41b8-921f-b87e4ef6b8dc · outbound

This paper cites DoRA: Weight-decomposed low-rank adaptation,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment DoRA: Weight-decomposed low-rank adaptation,

Reference 14

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Observation 8daaf14e-c364-4fc4-8826-61df1af6d98f · outbound

This paper cites When and why vision-language models behave like bags-of-words, and what to do about it?.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment When and why vision-language models behave like bags-of-words, and what to do about it?

Reference 15

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Observation 24415aea-59b0-4d02-a711-2fcf757b1fb2 · outbound

This paper cites Robust fine-tuning of zero-shot models,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Robust fine-tuning of zero-shot models,

Reference 16

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Observation d39d5fe0-49df-43cb-b1a7-e0731b559b5b · outbound

This paper cites Data filtering networks,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Data filtering networks,

Reference 17

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Observation 6d0e6292-82af-4548-95f5-d21db5e3b9d6 · outbound

This paper cites Meta CLIP 2: A Worldwide Scaling Recipe.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Meta CLIP 2: A Worldwide Scaling Recipe

Reference 18

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source=pdf_text observed=2026-08-01T01:32:32.988872Z digest=sha256:9d7b5844016b59700a6f63730a87b7dec5e22e9a5c3e5ff50d092a739065c362

Observation 757bf3f9-2c13-4fcc-ab7b-661a22738357 · outbound

This paper cites Gemma 4 31B Instruct,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Gemma 4 31B Instruct,

Reference 19

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Observation e028e063-5105-46da-8d61-23c2e401d404 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Representation Learning with Contrastive Predictive Coding

Reference 20

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Observation 1aea730e-f5c5-4f3f-be6b-ca7ceb03c6f2 · outbound

This paper cites Hugging Face Hub,.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Hugging Face Hub,

Reference 21

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Observation 769b9aa2-e3dd-4831-ba80-cba6f28b0042 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment Representation Learning with Contrastive Predictive Coding

Reference 2018

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Pith citing papers

No inbound Pith citation observations are available.