Paper Citation Record · LEDGER

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

As of 11 August 2026, this Paper Citation Record lists 100 of 111 outbound references and 6 inbound Pith citation observations for arXiv:2412.16243.

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

pith.paper-citation-record.v1
2412.16243 v1

Coverage vector

measured 100 of 111 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:32:54.293673Z

measured 106 of 106 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:06:13.722238Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T07:04:21.532153Z

Reference resolution

100 of 111 outbound references displayed

verified exact1
verified fuzzy25
unresolved74
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 67d842ef-4644-450c-a933-3017b622cdb0 · outbound

This paper cites Senior, Oriol Vinyals, and Andrew Zisserman.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Senior, Oriol Vinyals, and Andrew Zisserman

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.729277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa621a19-097a-42b2-b0bc-f7d7aa9d72b2 · outbound

This paper cites Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.735768Z

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Observation 796e6feb-ed8c-4558-9bae-aad63a5c8bc5 · outbound

This paper cites Art in the age of machine learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Art in the age of machine learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.741585Z

Source-reported events for the cited work

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Observation 2cdc397e-c7f4-4ab9-8378-9e9f754f1324 · outbound

This paper cites Uncertainty-based traffic accident anticipation with spatio-temporal relational learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Uncertainty-based traffic accident anticipation with spatio-temporal relational learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.747305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ac38b33-5bfa-43b0-9537-428351661a96 · outbound

This paper cites Food-101–mining discriminative components with random forests.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Food-101–mining discriminative components with random forests

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.752685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68faa9b3-3334-4680-a07f-014e805b30bb · outbound

This paper cites Early, intermediate and late fusion strategies for robust deep learning-based multimodal action recognition.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Early, intermediate and late fusion strategies for robust deep learning-based multimodal action recognition

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.757862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5134e87-08bb-4012-8cb3-cad72b608114 · outbound

This paper cites Language Models are Few-Shot Learners.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Language Models are Few-Shot Learners

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.763787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 261fbf57-7a12-4d42-b9cc-730b8004458a · outbound

This paper cites Tabtext: A flexible and contextual approach to tabular data representation.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Tabtext: A flexible and contextual approach to tabular data representation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.769612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 639cf92f-3417-4078-91e6-0cc5390ba52e · outbound

This paper cites Ensemble selection from libraries of models.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Ensemble selection from libraries of models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.775456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08b10916-2d2d-4195-a59f-a35ce9affb73 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data A simple framework for contrastive learning of visual representations

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.780839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f6068e2-8db0-4e4d-81cf-462599380cf7 · outbound

This paper cites Improved Baselines with Momentum Contrastive Learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Improved Baselines with Momentum Contrastive Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.787239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e4057b8-71cb-4af2-b788-88f9995ecb70 · outbound

This paper cites COVID-19 Image Data Collection: Prospective Predictions Are the Future.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data COVID-19 Image Data Collection: Prospective Predictions Are the Future

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.794899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bd3f2b5-a282-4a05-8e8d-cd4106c2a0f1 · outbound

This paper cites $i$-divergence geometry of probability distributions and minimization prob- lems.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data $i$-divergence geometry of probability distributions and minimization prob- lems

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.801417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10573258-6ad3-4072-88e8-dcc3d30b8a3c · outbound

This paper cites AutoAugment: Learning Augmentation Policies from Data.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data AutoAugment: Learning Augmentation Policies from Data

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.807106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 994d3633-e8ef-45ff-b5de-d26f8e89bff3 · outbound

This paper cites an unresolved cited work.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.812451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc36ce0b-0ec8-4ea7-802b-16d433a06cf6 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Qlora: Efficient finetuning of quantized llms

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.817344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 107e1337-f748-4dd8-91ba-83a8a219a578 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.822469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08d0cb6e-818c-426e-9856-3cc61f89ce63 · outbound

This paper cites SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-11T11:32:55.207323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dda2cfd4-5709-4bda-a4b2-1c58387f658f · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.832998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e85e74e6-4df9-4912-aebc-d38fb41a60b3 · outbound

This paper cites AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.838261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3b9aa09-e9ad-491c-ba5d-8f52d347f6a7 · outbound

This paper cites A proactive intelligent decision support system for predicting the popularity of online news.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data A proactive intelligent decision support system for predicting the popularity of online news

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.843828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efef5def-4c62-45aa-8122-98afc3a33efb · outbound

This paper cites Hyperparameter optimization.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Hyperparameter optimization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.849059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cea9fda4-fa6d-4f5e-97c9-8e62663a80df · outbound

This paper cites Auto-sklearn 2.0: Hands-free automl via meta-learning.Journal of Machine Learning Research, 23(261):1–61, 2022.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Auto-sklearn 2.0: Hands-free automl via meta-learning.Journal of Machine Learning Research, 23(261):1–61, 2022

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.854056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5411be2e-c825-4770-bab6-6ddc56c57bca · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.859092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24a3c495-e393-4ddf-9ed2-1ce71bfd0157 · outbound

This paper cites Early vs late fusion in multimodal convolutional neural networks.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Early vs late fusion in multimodal convolutional neural networks

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.870129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7cc3988-3a1d-437b-8cfb-3242639b6d42 · outbound

This paper cites What action causes this? towards naive physical action-effect prediction.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data What action causes this? towards naive physical action-effect prediction

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.875485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 929e744e-1ffc-490f-92db-ff55a189093a · outbound

This paper cites AMLB: an AutoML Benchmark.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data AMLB: an AutoML Benchmark

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.880682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 654a076e-013a-469c-be28-ec2cf48e79b6 · outbound

This paper cites Revisiting deep learning models for tabular data.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Revisiting deep learning models for tabular data

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.885810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a56bc0bd-83a6-4004-b398-b85026cabf8b · outbound

This paper cites A guide to machine learning for biologists.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data A guide to machine learning for biologists

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.891371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c358b2fe-91e0-491c-813c-ad7ee58906dc · outbound

This paper cites OneLLM: One Framework to Align All Modalities with Language.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data OneLLM: One Framework to Align All Modalities with Language

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.896453Z

Source-reported events for the cited work

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Observation 9348615c-d4a7-45e8-ad48-a75712c79e55 · outbound

This paper cites Sentiment analysis on large scale amazon product reviews.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Sentiment analysis on large scale amazon product reviews

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.902232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70554112-5a8f-4173-82ad-064afb51c429 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Momentum contrast for unsupervised visual representation learning

Reference 32

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Source-reported events for the cited work

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Observation 4791f039-b7cf-41fd-9e0b-66ba546c24b2 · outbound

This paper cites DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing

Reference 33

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Source-reported events for the cited work

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Observation 1cfb0f30-edc9-46ec-91b2-cb6e7f465234 · outbound

This paper cites Bag of tricks for image classification with convolutional neural networks.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Bag of tricks for image classification with convolutional neural networks

Reference 34

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Observation 441fd696-f34b-40e0-b510-ccf488512814 · outbound

This paper cites Tabllm: Few-shot classification of tabular data with large language models.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Tabllm: Few-shot classification of tabular data with large language models

Reference 35

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Source-reported events for the cited work

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Observation 572237be-d431-45e7-a86c-7a4785c04341 · outbound

This paper cites Dvm-car: A large-scale automotive dataset for visual marketing research and applications.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Dvm-car: A large-scale automotive dataset for visual marketing research and applications

Reference 36

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Source-reported events for the cited work

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Observation 59770186-8cc4-4a38-a2a4-2cec6603a478 · outbound

This paper cites Applying machine learning techniques to transporta- tion mode recognition using mobile phone sensor data.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Applying machine learning techniques to transporta- tion mode recognition using mobile phone sensor data

Reference 37

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Source-reported events for the cited work

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Observation 030607af-e0c7-49d8-8746-c13cec929aac · outbound

This paper cites Towards Better Serialization of Tabular Data for Few-shot Classification with Large Language Models.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Towards Better Serialization of Tabular Data for Few-shot Classification with Large Language Models

Reference 38

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Source-reported events for the cited work

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Observation 51e11593-2879-4a2c-a595-5668c71a743b · outbound

This paper cites Machine Learning in Chemistry, volume 1.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Machine Learning in Chemistry, volume 1

Reference 39

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Observation 98315d83-630a-4c37-888b-05ddf8b984a9 · outbound

This paper cites Autokeras: An automl library for deep learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Autokeras: An automl library for deep learning

Reference 40

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Observation f462f4e1-5087-4532-a407-7317e84d7d4c · outbound

This paper cites Bag of Tricks for Efficient Text Classification.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Bag of Tricks for Efficient Text Classification

Reference 41

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Observation 9cbfae1c-e978-465a-95ea-b3c9d6e185fc · outbound

This paper cites Rossi, and Andrea Prati.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Rossi, and Andrea Prati

Reference 42

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Source-reported events for the cited work

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Observation 79a387ed-5b79-4489-972f-6f9dc9fce65a · outbound

This paper cites Mahadi Hassan, Micah J.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Mahadi Hassan, Micah J

Reference 43

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Source-reported events for the cited work

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Observation dc43b165-7fcf-4b1c-8111-c927583710a4 · outbound

This paper cites The hateful memes challenge: Detecting hate speech in multimodal memes.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data The hateful memes challenge: Detecting hate speech in multimodal memes

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:53.980242Z

Source-reported events for the cited work

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Observation ddf48736-824f-48c8-b42f-6d2abcb18ed6 · outbound

This paper cites Vilt: Vision-and-language transformer without convolution or region supervision.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Vilt: Vision-and-language transformer without convolution or region supervision

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:56.104970Z

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Observation b25d6c8e-8384-4f28-b9f7-c77fb70506cb · outbound

This paper cites H2o automl: Scalable automatic machine learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data H2o automl: Scalable automatic machine learning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:56.088320Z

Source-reported events for the cited work

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Observation 2ec83341-e1bc-4951-b5a6-055ef5438e23 · outbound

This paper cites Multimodal prompting with missing modalities for visual recognition.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Multimodal prompting with missing modalities for visual recognition

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:56.070154Z

Source-reported events for the cited work

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Observation 271afd3b-3f5f-406f-96f3-c1ecae1b1f7d · outbound

This paper cites SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension

Reference 48

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Source-reported events for the cited work

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Observation 4a5128ce-3d2a-4511-9d15-4302682e67b7 · outbound

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Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:32:56.051239Z

Source-reported events for the cited work

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Observation deda5ee4-6a59-44db-96c1-8c8bb0e338a0 · outbound

This paper cites Multibench: Multiscale benchmarks for multimodal representation learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Multibench: Multiscale benchmarks for multimodal representation learning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:56.033366Z

Source-reported events for the cited work

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Observation 0ec7acda-1f63-48f5-b00a-c86774732196 · outbound

This paper cites Fast autoaugment.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Fast autoaugment

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:56.016345Z

Source-reported events for the cited work

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Observation e28bb484-2452-4c26-8b40-7a327ba5c2d5 · outbound

This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.999214Z

Source-reported events for the cited work

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Observation 585227d6-5c14-4124-bfa9-f23e629a0a83 · outbound

This paper cites Vision transform- ers are parameter-efficient audio-visual learners.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Vision transform- ers are parameter-efficient audio-visual learners

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.982049Z

Source-reported events for the cited work

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Observation 37266650-531e-4b8a-be8b-ff733551f224 · outbound

This paper cites Visual Instruction Tuning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Visual Instruction Tuning

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.034142Z

Source-reported events for the cited work

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Observation 7aa1e192-1da6-423c-b252-6cab0852ad95 · outbound

This paper cites On the Variance of the Adaptive Learning Rate and Beyond.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data On the Variance of the Adaptive Learning Rate and Beyond

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.039495Z

Source-reported events for the cited work

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Observation 56a2b851-9c1b-437a-a02c-5aced993e8b5 · outbound

This paper cites MMBench: Is Your Multi-modal Model an All-around Player?.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data MMBench: Is Your Multi-modal Model an All-around Player?

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.052111Z

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Observation dfd47099-105e-46b3-94ac-6c8a6375be11 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Swin transformer: Hierarchical vision transformer using shifted windows

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.057243Z

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Observation 79e8b68c-ef02-43fb-be46-293d1a820abc · outbound

This paper cites Learning Multimodal Data Augmentation in Feature Space.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Learning Multimodal Data Augmentation in Feature Space

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.062603Z

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Observation 26c2029f-2f25-4f5b-bb76-26b98f44cdc0 · outbound

This paper cites Decoupled Weight Decay Regularization.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Decoupled Weight Decay Regularization

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.067936Z

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Unavailable: canonical work link unavailable.

Observation 7f8f8ba0-9599-4b01-abe9-0da5ebd20e8c · outbound

This paper cites Smil: Multimodal learning with severely missing modality.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Smil: Multimodal learning with severely missing modality

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.936691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c26947db-c972-4a7b-8bd9-bba1b4d49332 · outbound

This paper cites Mixed Precision Training.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Mixed Precision Training

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.078179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8efadf71-34c8-4298-b635-abf46843c521 · outbound

This paper cites Trivialaugment: Tuning-free yet state-of-the-art data augmentation.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Trivialaugment: Tuning-free yet state-of-the-art data augmentation

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.919148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b2c5897c-e8b7-4baf-81ce-739119bfb311 · outbound

This paper cites r/Fakeddit: A New Multimodal Benchmark Dataset for Fine-grained Fake News Detection.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data r/Fakeddit: A New Multimodal Benchmark Dataset for Fine-grained Fake News Detection

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.090692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9323a766-8b24-496e-ac91-380f5bbf5002 · outbound

This paper cites Semi-supervised tabular classification via in-context learning of large language models.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Semi-supervised tabular classification via in-context learning of large language models

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.901583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b082bfb7-cdfe-4921-b872-fb86677304fb · outbound

This paper cites Multimodal deep learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Multimodal deep learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.884015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7e50974e-33e7-4f61-b1f2-a73e4663d1ff · outbound

This paper cites Tpot: A tree-based pipeline optimization tool for automating machine learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Tpot: A tree-based pipeline optimization tool for automating machine learning

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.865224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c9786abe-57ed-4d41-8cd5-e0d85312686f · outbound

This paper cites Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.114269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b68da2f9-4f2f-4fef-8da4-7848d5e8c87a · outbound

This paper cites Multilayer perceptron and neural networks.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Multilayer perceptron and neural networks

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.838768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 60220fcd-2b6a-4261-be0b-f6d51dec496f · outbound

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

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Learning transferable visual models from natural language supervision

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.124835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a9eb3e5-bf09-47f5-acc2-aecaf7604190 · outbound

This paper cites Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.131911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61420598-30c3-455f-b2b3-f912904c12c7 · outbound

This paper cites Bernstein, Alexander C.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Bernstein, Alexander C

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.811599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation afa69c84-fb28-4318-8aa3-fa192635ca25 · outbound

This paper cites an unresolved cited work.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:32:55.795175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 30cc74c4-34ff-4afa-9585-f323e6ea1eee · outbound

This paper cites Benchmarking Multimodal AutoML for Tabular Data with Text Fields.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Benchmarking Multimodal AutoML for Tabular Data with Text Fields

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.148693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 796e88c0-b2c9-4d74-a3fd-c37aac1266e1 · outbound

This paper cites Dropout: a simple way to prevent neural networks from overfitting.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Dropout: a simple way to prevent neural networks from overfitting

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.154110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 527bbdbf-a639-4432-bb44-614a9be96d56 · outbound

This paper cites Multimodn—multimodal, multi-task, interpretable modular networks.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Multimodn—multimodal, multi-task, interpretable modular networks

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.767564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6d52952a-7330-4820-a7fa-430aa8bfc1eb · outbound

This paper cites AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.164295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 255c333a-f098-4e15-a126-f3ec3ea03cb4 · outbound

This paper cites AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.169690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f7f1934-d4c1-4d23-b167-aae898e807e5 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.175116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ede8473f-9502-4db0-ae32-a8c68f265e81 · outbound

This paper cites The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.180398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c38ca31-a9ec-4f8a-a921-5420df5e9c55 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.751058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 585a7c11-03a1-46b2-92cd-a34c31516f0e · outbound

This paper cites LightAutoML: AutoML Solution for a Large Financial Services Ecosystem.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data LightAutoML: AutoML Solution for a Large Financial Services Ecosystem

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.191128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8260554-b9d8-462e-a3b1-863d3c0c0140 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Representation Learning with Contrastive Predictive Coding

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.196481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 712d444a-50f7-4db1-95af-27b7408d5386 · outbound

This paper cites OpenML: networked science in machine learning.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data OpenML: networked science in machine learning

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.201937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f11a5bf0-0640-446a-bed1-b3a1124db26e · outbound

This paper cites Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.733102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0715accd-0f47-4d56-a582-6a5e594fde6d · outbound

This paper cites Manifold mixup: Better representations by interpolating hidden states.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Manifold mixup: Better representations by interpolating hidden states

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.711628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ac76f888-fb12-4530-8bed-05c872d5377b · outbound

This paper cites Automatic detection of online recruitment frauds: Characteristics, methods, and a public dataset.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Automatic detection of online recruitment frauds: Characteristics, methods, and a public dataset

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.692020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7e4edae6-b118-4521-b85a-282f83dd03f4 · outbound

This paper cites Centralnet: a multilayer approach for multimodal fusion.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Centralnet: a multilayer approach for multimodal fusion

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.674908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0f3d1875-ce97-4a26-b41d-489c9ccd8c42 · outbound

This paper cites an unresolved cited work.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:32:55.658299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ace94817-0a93-4073-aa95-68f5d2b0a76e · outbound

This paper cites SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.233928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74ae649d-ff34-4877-ab3c-95881b555331 · outbound

This paper cites Flaml: A fast and lightweight automl library.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Flaml: A fast and lightweight automl library

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.640204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 823b05fb-60fd-4a96-b2ea-fa4c1c2057ff · outbound

This paper cites UniPredict: Large Language Models are Universal Tabular Classifiers.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data UniPredict: Large Language Models are Universal Tabular Classifiers

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.245525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dff76f85-c99a-4b7b-89d1-ff3a9da7a068 · outbound

This paper cites EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.251128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc6a3702-0d37-4ac9-96b1-299a9a450e69 · outbound

This paper cites Pytorch image models.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Pytorch image models

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.256764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cd66b8d-e55f-4ad0-9d70-6c1bc22063a6 · outbound

This paper cites Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.610663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2bd0a838-74df-4f3a-97b9-e8b6ec3a47d4 · outbound

This paper cites an unresolved cited work.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Unresolved cited work

Reference 95

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:32:55.592075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cc1e4a2e-145e-4686-a669-858c533dc5fb · outbound

This paper cites Modality-specific learning rates for effective multimodal additive late-fusion.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Modality-specific learning rates for effective multimodal additive late-fusion

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.572710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e02c73f7-eac5-4339-9233-c29527ee0c01 · outbound

This paper cites A Survey on Multimodal Large Language Models.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data A Survey on Multimodal Large Language Models

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.276444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 131f44ec-93a9-4417-9cbf-e1adc4b5fe32 · outbound

This paper cites MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-11T11:32:54.281677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ec59c4d-2848-4d1e-a12b-5036f0d31582 · outbound

This paper cites Multimodal price prediction.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Multimodal price prediction

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.552999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 58a44710-f7a3-463e-a462-bb0dac6f9fa3 · outbound

This paper cites Tag-assisted multimodal sentiment analysis under uncertain missing modalities.

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data Tag-assisted multimodal sentiment analysis under uncertain missing modalities

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:32:55.531118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation b6e713f0-8d1b-4438-a016-38e5aa82f808 · inbound

MultiModalPFN: Extending Prior-Data Fitted Networks for Multimodal Tabular Learning cites this paper.

MultiModalPFN: Extending Prior-Data Fitted Networks for Multimodal Tabular Learning Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-15T20:11:34.282727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6399dd01-cfb0-4982-9ea6-b316869f8382 · inbound

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning cites this paper.

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:56:27.032029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 29358c85-fa39-46ff-bc69-c403ceca74f2 · inbound

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning cites this paper.

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-21T00:33:52.793869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 00bc0266-ace6-4ef3-9f9a-0f193817ce35 · inbound

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image cites this paper.

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 98

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T05:51:24.761694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4b6447a8-0f1d-4304-b2c6-a18ccbe7be48 · inbound

Beyond IID: How General Are Tabular Foundation Models, Really? cites this paper.

Beyond IID: How General Are Tabular Foundation Models, Really? Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 117

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:04:21.534599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 21d84596-18cd-4ae8-a670-159a501a9e44 · inbound

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning cites this paper.

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T18:06:13.722238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.