Pith. sign in

Paper Citation Record · LEDGER

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection

As of 17 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2502.08687.

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

pith.paper-citation-record.v1
2502.08687 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:29:33.158193Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

23 of 23 outbound references displayed

  • verified exact16
  • verified fuzzy1
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce2d9286-280f-4bd4-a26d-45a5613f8fcb · outbound

This paper cites Quality assessment of some food products in iraq,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Quality assessment of some food products in iraq,

Reference 2

Resolution
verified exact
doi, observed 2026-08-08T05:29:33.417773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.047080Z digest=sha256:cba526b1b3d317bb3a3eb773de681b36e34ad38aa2822ece163f1f6f9e7c054d

Observation 0e4d5859-5250-46f6-8f60-e5f2d1340d6b · outbound

This paper cites Food safety, a global challenge,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Food safety, a global challenge,

Reference 3

Resolution
verified exact
doi, observed 2026-08-08T05:29:33.401766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.051894Z digest=sha256:1f762b9904dda8366150f4b0f163175a70e6abfae66386bae28ac0df8571c251

Observation 6d532ea7-b51c-40ae-8c77-c91167b249e7 · outbound

This paper cites Critical review of methods for risk ranking of food-related hazards, based on risks for human health,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Critical review of methods for risk ranking of food-related hazards, based on risks for human health,

Reference 4

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-08T05:29:34.421968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.057702Z digest=sha256:4f43582e04bb430e2c0fcc9fd83bb65ec712f93123935ee6be705667465745c3

Observation 34cafd91-09db-433d-9dca-a7e9d6f3e1d6 · outbound

This paper cites Report on the development of a food classification and description system for exposure assessment and guidance on its implementation and use,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Report on the development of a food classification and description system for exposure assessment and guidance on its implementation and use,

Reference 5

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-08T05:29:34.214401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.063753Z digest=sha256:56e1af9f8bae27094975e6fa624c2e80ce934c3859cdd937afec14205761e835

Observation 5a04e319-60f9-47b8-af54-26ad612c3b61 · outbound

This paper cites Explainable artificial intelligence: an analytical review,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Explainable artificial intelligence: an analytical review,

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-08T05:29:33.068813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:29:33.068813Z digest=sha256:8a0ded859b1fc2b074aad11be5851621b7ac66e0a2e1b93395fc35e34cddbcb1

Observation f48b936c-6600-49b9-adfa-57067f2b2364 · outbound

This paper cites A survey of current practice and teaching of ai,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection A survey of current practice and teaching of ai,

Reference 7

Resolution
verified exact
doi, observed 2026-08-08T05:29:33.374468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.074507Z digest=sha256:ba1f3c9fea7c4f0ff77f7f897fc0603a75a4e71ae5a9390c0066ba744d05a9ec

Observation 4a3971e6-38b0-454b-9f37-18a65927f7e0 · outbound

This paper cites TaskComplexity: A Dataset for Task Complexity Classification with In-Context Learning, FLAN-T5 and GPT-4o Benchmarks.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection TaskComplexity: A Dataset for Task Complexity Classification with In-Context Learning, FLAN-T5 and GPT-4o Benchmarks

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-08T05:29:34.007711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.079372Z digest=sha256:f50e83e2c3a30e42ae96b8f0bf399e80fe228a8f3f0e04a7f2a5df4540d08470

Observation 32e0825b-8863-48b4-a052-1811453d26fe · outbound

This paper cites Exploring in-context learning: A deep dive into model size, templates, and few-shot learning for text classification,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Exploring in-context learning: A deep dive into model size, templates, and few-shot learning for text classification,

Reference 9

Resolution
verified exact
doi, observed 2026-08-08T05:29:33.358630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.084618Z digest=sha256:0a4e5da9967fcd44edc9e97e8251424e1c2bc2beafbdb856783c391b54c1bd78

Observation c7130af0-71b4-40ea-91c6-a15d63e46c90 · outbound

This paper cites Mashee at SemEval-2024 Task 8: The Impact of Samples Quality on the Performance of In-Context Learning for Machine Text Classification.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Mashee at SemEval-2024 Task 8: The Impact of Samples Quality on the Performance of In-Context Learning for Machine Text Classification

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-08T05:29:33.984529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.089489Z digest=sha256:0b1e9e907df56e09617db97d976c04491f9b00d0ceb583881f5896db589afb34

Observation 78942330-288e-42c8-9eda-c4ec325636e4 · outbound

This paper cites Arabic offensive language classification: Leveraging transformer, lstm, and svm,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Arabic offensive language classification: Leveraging transformer, lstm, and svm,

Reference 11

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-08T05:29:33.961739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.094588Z digest=sha256:47d5265affd315373bd0f94d5355f6b01916b73a2e8d985fa4dc3fbb9678f749

Observation 06e19c2b-81e4-4ad2-9122-9307ab89a099 · outbound

This paper cites A Survey of Large Language Models.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection A Survey of Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-08T05:29:33.099631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:29:33.099631Z digest=sha256:a6abba271678990294fcebb792a878e54d5f867f1f40202ffdcc249a0c81a90f

Observation c2ca123c-a7ed-45f3-b1fb-42aed03ae9f2 · outbound

This paper cites Deep learning approaches for question answering system,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Deep learning approaches for question answering system,

Reference 13

Resolution
verified exact
doi, observed 2026-08-08T05:29:33.326484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.104798Z digest=sha256:f43ca488981dc17796e0c8776db9dbb23d245850e16b42f9ee7560faaedbe165

Observation fb29c788-b7b3-4250-bc2c-748dc7e70b9b · outbound

This paper cites Research and implementation of english grammar check and error correction based on deep learning,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Research and implementation of english grammar check and error correction based on deep learning,

Reference 14

Resolution
verified exact
doi, observed 2026-08-08T05:29:33.310181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.109614Z digest=sha256:a467932339b46fc0ba76a459d5cabe50571b870070947a8fcb64bd6ad9b98cbc

Observation 873a3b13-9a7a-4fa3-b6b1-cf16b3534732 · outbound

This paper cites A survey on data augmentation for text classification,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection A survey on data augmentation for text classification,

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-08T05:29:33.114525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:29:33.114525Z digest=sha256:c1671064f13e6d8c2699961908b84b9cefe1069c589411b603ef4f2bef2b7d83

Observation 9f0ccb19-73fd-4e1a-b39e-224ae694c7d7 · outbound

This paper cites T5 for hate speech, augmented data, and ensemble,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection T5 for hate speech, augmented data, and ensemble,

Reference 16

Resolution
verified exact
doi, observed 2026-08-08T05:29:33.282015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.119326Z digest=sha256:db9e0215b1b74108db4ae8eb12ca6e13cc9576691c35cd2487930496495067a3

Observation 457110c3-7741-4212-8770-7a666e9221d1 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-08T05:29:33.124217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:29:33.124217Z digest=sha256:df9d81a8ac7cada814115fd363444f2ca7f8a94f970979ac06dc92c70d063d65

Observation 176868c3-e954-471e-ab35-f6f07f75edc5 · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Scaling Instruction-Finetuned Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-08T05:29:33.129326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:29:33.129326Z digest=sha256:0813bb253fff94efd1fcda3b36567f3a889e814ea900996f94069892896c1370

Observation 810e5d35-8c9e-4405-b9f8-266629b161c7 · outbound

This paper cites Chatgpt: open possibilities,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Chatgpt: open possibilities,

Reference 19

Resolution
verified exact
doi, observed 2026-08-08T05:29:33.248367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.134358Z digest=sha256:5cd6559aef4266f7d16c8b9ed4b5ede0c53a6f173865d63d9254c399f0cad3f3

Observation 7cfe9f0b-0de6-47c4-be2b-ba5f9be4a31b · outbound

This paper cites Study and analysis of chat gpt and its impact on different fields of study,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Study and analysis of chat gpt and its impact on different fields of study,

Reference 20

Resolution
verified exact
doi, observed 2026-08-08T05:29:33.232285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.138917Z digest=sha256:b5d1f81eb347e5c8cf174c9b71b77e79df2c6e95e38c178b5c97c9c6913e91dc

Observation 240bc49b-f6c0-422a-8613-569afe31e3c5 · outbound

This paper cites How chatgpt works: a mini review,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection How chatgpt works: a mini review,

Reference 21

Resolution
verified exact
doi, observed 2026-08-08T05:29:33.215418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.143618Z digest=sha256:7b2c31599807da6bbf9bb7b2a05f526de09d7e3173285b98b10c67da9449fcb0

Observation e780f3c4-5dba-4305-9db9-2cf6cab7d089 · outbound

This paper cites A comparative analysis of encoder only and decoder only models for challenging llm-generated stem mcqs using a self-evaluation approach,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection A comparative analysis of encoder only and decoder only models for challenging llm-generated stem mcqs using a self-evaluation approach,

Reference 22

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-08T05:29:33.705547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.148432Z digest=sha256:154f4e431780c9ef5d7a2519fbb072dfc760ef01d622ecda35a58d2fa5d2af67

Observation 10ceda0f-50f1-4c70-8f5c-b94d47b59b6a · outbound

This paper cites Attention Is All You Need.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Attention Is All You Need

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-08T05:29:33.153062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:29:33.153062Z digest=sha256:7eb27a630373fc096d2b4e9191627557578dcb70bbef703b49852cddde3077b4

Observation c15d680f-5f27-4b88-aaa1-7d2113b9889d · outbound

This paper cites Food hazard detection semeval 2025 github repository,.

Data Augmentation to Improve Large Language Models in Food Hazard and Product Detection Food hazard detection semeval 2025 github repository,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T05:29:34.533147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-08T05:29:33.158193Z digest=sha256:c0ef36cbf40a8e01e1fc7f022c6342cc21ba77580733ea527ebf5aa2511c27d3

Pith citing papers

No inbound Pith citation observations are available.