Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:53:30.508953Z
Paper Citation Record · LEDGER
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights
As of 22 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 0 inbound Pith citation observations for arXiv:2507.04412.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
65 of 65 outbound references displayed
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- verified fuzzy50
- unresolved10
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation cd67c55a-805a-4941-b87b-1e6310ee3be4 · outbound
This paper cites Fruitq: a new dataset of multiple fruit images for freshness evaluation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Fruitq: a new dataset of multiple fruit images for freshness evaluation
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 21d3c249-8a86-417e-ad86-1fbccc82679b · outbound
This paper cites Live to eat and eat to live longer.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Live to eat and eat to live longer
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f0ad4be2-2bd7-4f7b-a3f4-addacd6dfd6d · outbound
This paper cites Products-10K: A Large-scale Product Recognition Dataset.
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
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Source-reported events for the cited work
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Observation b606cedb-a9de-4038-87dc-9d6ad317d717 · outbound
This paper cites Recipenlg: A cooking recipes dataset for semi-structured text generation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Recipenlg: A cooking recipes dataset for semi-structured text generation
Reference 4
- Resolution
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Source-reported events for the cited work
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Observation a02941e6-233f-4f96-9d14-5db765c7ce2e · outbound
This paper cites Food-101 – mining discriminative components with random forests.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Food-101 – mining discriminative components with random forests
Reference 5
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 1192db75-84ba-49b4-a419-65b5d74653b5 · outbound
This paper cites Food-101–mining discriminative components with random forests.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Food-101–mining discriminative components with random forests
Reference 6
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 915d8674-0fc3-4836-a6a6-1e82ee673fc2 · outbound
This paper cites Bs-nets: An end- to-end framework for band selection of hyperspectral image.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Bs-nets: An end- to-end framework for band selection of hyperspectral image
Reference 7
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6e1863e3-b0c1-4618-8633-c68fd1a15e96 · outbound
This paper cites Cascade r-cnn: High quality object detection and instance segmentation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Cascade r-cnn: High quality object detection and instance segmentation
Reference 8
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation cf6bb4c1-e44a-4f63-857c-2df9893b8e1b · outbound
This paper cites Deep-based ingredi- ent recognition for cooking recipe retrieval.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Deep-based ingredi- ent recognition for cooking recipe retrieval
Reference 9
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ac2b869c-e48e-4288-9850-efa720ac09c7 · outbound
This paper cites Hybrid task cascade for instance seg- mentation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Hybrid task cascade for instance seg- mentation
Reference 10
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation e15b7d9e-d6f8-43db-88f4-45affa915a1e · outbound
This paper cites Beverage products packaging dataset for auto- matic shelf recognition and its application.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Beverage products packaging dataset for auto- matic shelf recognition and its application
Reference 11
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f91378ed-08d4-46dd-b6b7-4017f8f3c1b0 · outbound
This paper cites Fire: Food image to recipe generation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Fire: Food image to recipe generation
Reference 12
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ac3c4f76-364e-4167-a5b0-31cd822b9dcb · outbound
This paper cites A low-shot object counting network with iterative prototype adaptation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights A low-shot object counting network with iterative prototype adaptation
Reference 13
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c83bc18c-0b7f-4459-994d-a65ce41fe839 · outbound
This paper cites Retrieval and classi- fication of food images.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Retrieval and classi- fication of food images
Reference 14
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 77230496-02f0-4345-bf9a-7cba348edf55 · outbound
This paper cites MetaFood CVPR 2024 Challenge on Physically Informed 3D Food Reconstruction: Methods and Results.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights MetaFood CVPR 2024 Challenge on Physically Informed 3D Food Reconstruction: Methods and Results
Reference 15
- Resolution
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Source-reported events for the cited work
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Observation 53788b3a-0429-4150-8279-474062e8303a · outbound
This paper cites Mask r-cnn.
Reference 16
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f4a36621-0aee-4fa1-bd05-7e9709d0cd52 · outbound
This paper cites Learning to Count Anything: Reference-less Class-agnostic Counting with Weak Supervision.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Learning to Count Anything: Reference-less Class-agnostic Counting with Weak Supervision
Reference 17
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation af555b54-8fda-49e5-8dd6-7fa72c130401 · outbound
This paper cites Vegfru: A domain-specific dataset for fine-grained visual categoriza- tion.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Vegfru: A domain-specific dataset for fine-grained visual categoriza- tion
Reference 18
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation a210059f-a7bd-40fc-9ded-6fdf8970425f · outbound
This paper cites One-shot neu- ral band selection for spectral recovery.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights One-shot neu- ral band selection for spectral recovery
Reference 19
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 54d6d49d-4b18-4f0b-b0a8-40277d67cd46 · outbound
This paper cites Mask scoring r-cnn.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Mask scoring r-cnn
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:39.957205Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 8af477e4-f0b9-4ebf-b8b0-a88bbf533ab0 · outbound
This paper cites CWD30: A Comprehensive and Holistic Dataset for Crop Weed Recognition in Precision Agriculture.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights CWD30: A Comprehensive and Holistic Dataset for Crop Weed Recognition in Precision Agriculture
Reference 21
- Resolution
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Source-reported events for the cited work
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Observation e3d4a9e6-7666-432a-acbf-c3d9f41cf6c9 · outbound
This paper cites Visible imaging to convolutionally discern and authenticate varieties of rice and their derived flours.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Visible imaging to convolutionally discern and authenticate varieties of rice and their derived flours
Reference 22
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 74b033b2-88f1-465f-b6e8-e1c5920645c9 · outbound
This paper cites RoDE: Linear Rectified Mixture of Diverse Experts for Food Large Multi-Modal Models.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights RoDE: Linear Rectified Mixture of Diverse Experts for Food Large Multi-Modal Models
Reference 23
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2df4da36-6feb-4261-bb96-8608bf476906 · outbound
This paper cites FoodX-251: A Dataset for Fine-grained Food Classification.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights FoodX-251: A Dataset for Fine-grained Food Classification
Reference 24
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation e82665b2-9998-4311-bc46-725cee684806 · outbound
This paper cites Automatic expansion of a food image dataset leveraging existing categories with domain adaptation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Automatic expansion of a food image dataset leveraging existing categories with domain adaptation
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:39.494175Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 98e40872-d594-4ece-b25b-dd867aa6d70a · outbound
This paper cites A hierarchical grocery store image dataset with visual and se- mantic labels.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights A hierarchical grocery store image dataset with visual and se- mantic labels
Reference 26
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation db3cc303-bb6a-401d-92a4-10614c58fe16 · outbound
This paper cites CounTR: Transformer-based Generalised Visual Counting.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights CounTR: Transformer-based Generalised Visual Counting
Reference 27
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 655a8b2f-c5bb-4212-bc1b-757acbce9bb9 · outbound
This paper cites Ingredient prediction via context learn- ing network with class-adaptive asymmetric loss.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Ingredient prediction via context learn- ing network with class-adaptive asymmetric loss
Reference 28
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation fca39ed9-5124-4894-bbcf-16ec3630a1d5 · outbound
This paper cites Recipe1m+: A dataset for learning cross-modal embeddings for cooking recipes and food images.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Recipe1m+: A dataset for learning cross-modal embeddings for cooking recipes and food images
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 1932c532-7b48-48d7-9228-b1e13c1dbfb8 · outbound
This paper cites Fruitnet: Indian fruits im- age dataset with quality for machine learning applications.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Fruitnet: Indian fruits im- age dataset with quality for machine learning applications
Reference 30
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 7897c78d-d13b-409e-8bb8-ea5e06cd0ef6 · outbound
This paper cites Isia food- 500: A dataset for large-scale food recognition via stacked global-local attention network.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Isia food- 500: A dataset for large-scale food recognition via stacked global-local attention network
Reference 31
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 4791b073-32e1-458b-a08a-3c84b0f8d35b · outbound
This paper cites Large scale visual food recognition.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Large scale visual food recognition
Reference 32
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ae1c6187-3828-44d9-8a00-8456315337df · outbound
This paper cites Fruits-262 dataset: A dataset containing a vast majority of the popular and known fruits, 2021.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Fruits-262 dataset: A dataset containing a vast majority of the popular and known fruits, 2021
Reference 33
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b5be9c7a-0031-4bf5-a487-572ff06d40d1 · outbound
This paper cites Using deep learning for image-based plant disease detection.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Using deep learning for image-based plant disease detection
Reference 34
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ddfa4779-5c8c-4ba7-8508-a9fc71506a73 · outbound
This paper cites Llava-chef: A multi- modal generative model for food recipes.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Llava-chef: A multi- modal generative model for food recipes
Reference 35
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation bc9170a9-f3c8-44fd-b9d0-ff195124fb95 · outbound
This paper cites Omnicount: Multi-label object count- ing with semantic-geometric priors.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Omnicount: Multi-label object count- ing with semantic-geometric priors
Reference 36
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 049ee9d8-8b9c-40a1-b0f5-bc644c97a5c8 · outbound
This paper cites Terrace-based food counting and segmentation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Terrace-based food counting and segmentation
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:37.312089Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 80585f7e-3df5-4ad7-8ff0-6c3b10f081c3 · outbound
This paper cites Sibnet: Food instance counting and segmentation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Sibnet: Food instance counting and segmentation
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:37.069751Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation eb867692-bfd8-4f6e-8caf-25413ae47dee · outbound
This paper cites Honey dataset stan- dard using hyperspectral imaging for machine learning prob- lems.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Honey dataset stan- dard using hyperspectral imaging for machine learning prob- lems
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:36.791037Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 3ff5d256-b4b2-4a24-9452-d21d213f5753 · outbound
This paper cites Uec-foodpix complete: A large-scale food image segmentation dataset.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Uec-foodpix complete: A large-scale food image segmentation dataset
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:36.510028Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 7fcfcdcf-f1b4-4cf9-b033-2d757bfaa3dc · outbound
This paper cites Foodd: food detection dataset for calorie mea- surement using food images.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Foodd: food detection dataset for calorie mea- surement using food images
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:36.345918Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 505413ff-667f-4a50-beac-fec92ff09a79 · outbound
This paper cites Learning to count everything.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Learning to count everything
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:36.194324Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 1b3757c7-869b-4e61-9e7d-5f390cb534d0 · outbound
This paper cites Leveraging automatic personalised nutrition: food image recognition benchmark and dataset based on nutrition taxonomy.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Leveraging automatic personalised nutrition: food image recognition benchmark and dataset based on nutrition taxonomy
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:35.961390Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation a021bfa3-e0a4-4b9c-a568-14886c1a261b · outbound
This paper cites Multi-task learn- ing for calorie prediction on a novel large-scale recipe dataset enriched with nutritional information.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Multi-task learn- ing for calorie prediction on a novel large-scale recipe dataset enriched with nutritional information
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:35.728195Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 3b33dd40-68da-4aea-a358-0918a7107ddf · outbound
This paper cites Represent, compare, and learn: A similarity-aware framework for class-agnostic counting.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Represent, compare, and learn: A similarity-aware framework for class-agnostic counting
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:35.574649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 89722a38-d672-4e04-8177-9d8b45ce0b77 · outbound
This paper cites Plantdoc: A dataset for visual plant disease detection.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Plantdoc: A dataset for visual plant disease detection
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:35.323633Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 17a11e7b-2365-4dc8-9d78-6f6e871ccc3e · outbound
This paper cites The cropandweed dataset: A multi-modal learning approach for efficient crop and weed manipulation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights The cropandweed dataset: A multi-modal learning approach for efficient crop and weed manipulation
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:53:28.672510Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9eaa3be0-5a8d-4cc0-af57-c31be66bebc7 · outbound
This paper cites NutritionVerse-3D: A 3D Food Model Dataset for Nutritional Intake Estimation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights NutritionVerse-3D: A 3D Food Model Dataset for Nutritional Intake Estimation
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T19:53:30.885920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b9550a4e-862b-4d03-a479-56fe48089bd0 · outbound
This paper cites Classification of biscuit defect states and foreign objects using cnn-based features.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Classification of biscuit defect states and foreign objects using cnn-based features
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:35.087350Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 355f910f-24d0-466b-af96-bdcb2cf9445e · outbound
This paper cites Nutrition5k: To- wards automatic nutritional understanding of generic food.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Nutrition5k: To- wards automatic nutritional understanding of generic food
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:34.852539Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c0309ff0-86cf-4bde-9ae6-20c746f2497c · outbound
This paper cites Rice seedling detection in uav images using transfer learning and machine learning.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Rice seedling detection in uav images using transfer learning and machine learning
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:34.661513Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation de0a6269-a8f4-4808-a1f1-48d221ed31ec · outbound
This paper cites Solov2: Dynamic and fast instance segmenta- tion.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Solov2: Dynamic and fast instance segmenta- tion
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:34.394415Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c7ded2d5-9f00-4262-b816-cf90a767323c · outbound
This paper cites Multi-state ingredient recognition via adaptive multi-centric network.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Multi-state ingredient recognition via adaptive multi-centric network
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:34.229069Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation bdfc3e80-2140-4118-b0b3-b034fa791bcf · outbound
This paper cites Automatic counting of in situ rice seedlings from uav images based on a deep fully convolutional neural network.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Automatic counting of in situ rice seedlings from uav images based on a deep fully convolutional neural network
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:34.027399Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 1d793bfb-7af9-4384-9797-6ceae18f0e74 · outbound
This paper cites A large-scale benchmark for food im- age segmentation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights A large-scale benchmark for food im- age segmentation
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:33.761871Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation a2377af5-c08e-46bb-b898-1abb3dbe559e · outbound
This paper cites Hsifoodingr-64: A dataset for hyperspectral food-related studies and a benchmark method on food ingredient retrieval.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Hsifoodingr-64: A dataset for hyperspectral food-related studies and a benchmark method on food ingredient retrieval
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:33.503989Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 2fc314d1-32f5-4dbc-bc48-0b40635357c3 · outbound
This paper cites Multiple attentional pyra- mid networks for chinese herbal recognition.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Multiple attentional pyra- mid networks for chinese herbal recognition
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:33.312453Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 54e9e856-c769-4a4c-a3fa-02ba0df1f4d4 · outbound
This paper cites FoodLMM: A Versatile Food Assistant using Large Multi-modal Model.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights FoodLMM: A Versatile Food Assistant using Large Multi-modal Model
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:53:29.966947Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bdc040f6-15b7-47d0-8e33-c3ad6c81a8f3 · outbound
This paper cites Fine-grained image classifi- cation by exploring bipartite-graph labels.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Fine-grained image classifi- cation by exploring bipartite-graph labels
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:33.027010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 63074190-482e-4b65-af61-83c56394b3f4 · outbound
This paper cites FoodSky: A Food-oriented Large Language Model that Passes the Chef and Dietetic Examination.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights FoodSky: A Food-oriented Large Language Model that Passes the Chef and Dietetic Examination
Reference 60
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T19:53:30.698067Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation eebb64af-2f74-4a5d-8395-05255c607a05 · outbound
This paper cites Learn more for food recognition via progressive self-distillation.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Learn more for food recognition via progressive self-distillation
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:32.796328Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation bba88002-894d-4fa0-b8cc-4480198e88ca · outbound
This paper cites It is worth noting that these categories do not represent all foods.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights It is worth noting that these categories do not represent all foods
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:32.611162Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 8cc279fd-271d-41cc-9b8e-42cbb916967b · outbound
This paper cites an unresolved cited work.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Unresolved cited work
Reference 63
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T19:53:32.362474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 10e8cd40-c7fe-4a6a-bb04-22de95b0e843 · outbound
This paper cites 2), we have obtained spectral data with wavelength between 400 nm to 1020 nm shown in Table 8.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights 2), we have obtained spectral data with wavelength between 400 nm to 1020 nm shown in Table 8
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:53:32.141100Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 566bf4cc-965e-4d73-8b88-6f96a0bcabf7 · outbound
This paper cites an unresolved cited work.
SFOOD: A Multimodal Benchmark for Comprehensive Food Attribute Analysis Beyond RGB with Spectral Insights Unresolved cited work
Reference 65
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T19:53:31.851022Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Pith citing papers
No inbound Pith citation observations are available.