Paper Citation Record · LEDGER

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion

As of 10 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.25820.

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

pith.paper-citation-record.v1
2607.25820 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T01:26:09.263058Z

measured 25 of 25 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 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

25 of 25 outbound references displayed

verified exact0
verified fuzzy0
unresolved25
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3127a464-8430-4580-b8d7-3c34ee9500c9 · outbound

This paper cites Swin-TUNA : A Novel PEFT Approach for Accurate Food Image Segmentation.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion Swin-TUNA : A Novel PEFT Approach for Accurate Food Image Segmentation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.001027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 172aa03d-a6c9-453f-be96-a893e6f5a8c5 · outbound

This paper cites Journal of Imaging10(12) (2024).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion Journal of Imaging10(12) (2024)

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.164736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73ee12ce-c8ba-4b24-9958-821a73539932 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelli- gence40(4), 834–848 (2017).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion IEEE Transactions on Pattern Analysis and Machine Intelli- gence40(4), 834–848 (2017)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.307660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57200921-6b59-429d-8b0d-4a6fd4e464f7 · outbound

This paper cites In: Proceedings of European Conference on Computer Vision (2020).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of European Conference on Computer Vision (2020)

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.433312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e25e9438-f55f-4493-9afe-adeff8fdbc70 · outbound

This paper cites In: Proceedings of IEEE/CVF International Conference on Computer Vision and Pattern Recognition.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of IEEE/CVF International Conference on Computer Vision and Pattern Recognition

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.562077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50922c07-f0fa-4026-a9dc-8ae765196ccc · outbound

This paper cites an unresolved cited work.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.693765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dbdd71e-a035-4b84-bc7c-9668a6d3ada1 · outbound

This paper cites In: Proceedings of Annual Con- ference of the North American Chapter of the Association for Computational Lin- guistics: Human Language Technologies.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of Annual Con- ference of the North American Chapter of the Association for Computational Lin- guistics: Human Language Technologies

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.835649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae1a0681-36b1-48b0-a3e3-2bf362fbbd19 · outbound

This paper cites In: Proceedings of International Conference on Learning Representations (2021).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of International Conference on Learning Representations (2021)

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:06.964329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5f37b4f-cbf6-4d79-8548-7bdeb0c3464e · outbound

This paper cites Segment Anything.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion Segment Anything

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.091194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4341735a-0ebd-41e9-96a6-017dfc20aa77 · outbound

This paper cites FoodSAM: Any Food Segmentation.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion FoodSAM: Any Food Segmentation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.240062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbc88985-7e46-4c61-8043-bb53374cedba · outbound

This paper cites In: Proceedings of Advances in Neural Information Processing Systems (2023).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of Advances in Neural Information Processing Systems (2023)

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.376322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff922d91-7742-47c3-8379-361e0d966cd8 · outbound

This paper cites an unresolved cited work.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.518465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 688e2617-e620-46dc-94af-74c0e5e13bb5 · outbound

This paper cites In: Proceedings of International Conference on Learning Representations (2017).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of International Conference on Learning Representations (2017)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.649322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5a4a994-a663-4bf4-92e4-d8fe168dd647 · outbound

This paper cites In: Proceedings of International Conference on Neural Information Processing Systems (2019).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of International Conference on Neural Information Processing Systems (2019)

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.816037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2459360-da69-40ba-bc8f-b335b7b987ea · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence43(1), 187–203 (2021).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion IEEE Transactions on Pattern Analysis and Machine Intelligence43(1), 187–203 (2021)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:07.984727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9001d023-754a-4a00-9d84-7abb09a988d0 · outbound

This paper cites GPT-4 Technical Report.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion GPT-4 Technical Report

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:08.153343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e58ac940-fc64-495a-9483-9f90f07e83aa · outbound

This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:08.285873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9cfaced-b4d8-4165-9d34-8de6c82b7575 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion Learning Transferable Visual Models From Natural Language Supervision

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:08.368028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2439946e-4cc6-4209-84d4-cdf88ff5b0aa · outbound

This paper cites Transferring Knowledge for Food Image Segmentation using Transformers and Convolutions.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion Transferring Knowledge for Food Image Segmentation using Transformers and Convolutions

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:08.436849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f741501e-1e76-4c12-9c8f-38c30a467865 · outbound

This paper cites In: Proceedings of ACM International Conference on Multimedia.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of ACM International Conference on Multimedia

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:08.546641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb7f6f68-c5d4-41da-a498-87602296c94b · outbound

This paper cites In: Proceedings of IEEE/CVF International Conference on Computer Vision and Pattern Recogni- tion.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of IEEE/CVF International Conference on Computer Vision and Pattern Recogni- tion

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:08.654137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 723266d5-8813-40c0-894d-336c7749b83c · outbound

This paper cites In: Proceedings of European Conference on Computer Vision (2018).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of European Conference on Computer Vision (2018)

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:08.794479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84120ea1-ce41-4add-afcb-f883553d8d4b · outbound

This paper cites In: Proceedings of Annual Conference on Neural Information Processing Systems (2021).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of Annual Conference on Neural Information Processing Systems (2021)

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:08.957203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3462cf0-cc06-43c8-b4f9-0f3b135101c0 · outbound

This paper cites In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2017).

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2017)

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:09.072655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e743908f-aefd-4c23-9ea9-a2b898fbeecf · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

Food Image Segmentation with LLM-Derived Ingredient Labels and Multimodal Fusion MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:09.263058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.