Paper Citation Record · LEDGER

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings

As of 10 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2506.01587.

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

pith.paper-citation-record.v1
2506.01587 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:42:53.606510Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:39:42.728087Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T00:39:45.260557Z

Reference resolution

38 of 38 outbound references displayed

verified exact12
verified fuzzy7
unresolved11
parse uncertain0
malformed identifier2
metadata mismatch6

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0366bc8f-a577-4095-a367-6b5c1154a975 · outbound

This paper cites Fake news detection on Pakistani news using machine learning and deep learning,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Fake news detection on Pakistani news using machine learning and deep learning,

Reference 1

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T11:42:55.129327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a34724b-1c60-4426-8ac3-dab660f350d2 · outbound

This paper cites Urdu- Fake@FIRE2020: Shared Track on Fake News Identification in Urdu,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Urdu- Fake@FIRE2020: Shared Track on Fake News Identification in Urdu,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T11:42:53.402857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 071c63a8-4eb4-4a0d-9a4b-37e46e7bafc5 · outbound

This paper cites Ur Rehman Ahmed, A.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Ur Rehman Ahmed, A

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T11:42:53.408548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 170d5e47-696b-4057-9b5b-351a063652c2 · outbound

This paper cites RumorLLM: A Rumor Large Language Model-Based Fake-News-Detection Data-Augmentation Approach,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings RumorLLM: A Rumor Large Language Model-Based Fake-News-Detection Data-Augmentation Approach,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T11:42:53.413992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a757ed41-400a-4f65-9a79-403bd9138396 · outbound

This paper cites Ax-to-Grind Urdu: Benchmark Dataset for Urdu Fake News Detection.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Ax-to-Grind Urdu: Benchmark Dataset for Urdu Fake News Detection

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:42:55.339297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 46f9ed76-d5e5-470d-8493-8a871d6ee417 · outbound

This paper cites & Che, D.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings & Che, D

Reference 6

Resolution: malformed identifier; doi_truncated, observed 2026-08-07T11:42:53.855101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e67a1d88-86c3-4767-8624-a187d525f5cd · outbound

This paper cites Discerning truth from deception: Human judgments and automation efforts,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Discerning truth from deception: Human judgments and automation efforts,

Reference 7

Resolution: verified exact; doi, observed 2026-08-07T11:42:53.836456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 27aeb0a5-d7cc-46d3-a8b3-8422792c31d2 · outbound

This paper cites The roles of liar inten- tion, lie content, and theory of mind in children’s evaluation of lies,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings The roles of liar inten- tion, lie content, and theory of mind in children’s evaluation of lies,

Reference 8

Resolution: verified exact; doi, observed 2026-08-07T11:42:53.817867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 67d5d452-bf66-40ff-9625-db85c34a999e · outbound

This paper cites Fake News or Truth? Using Satirical Cues to Detect Potentially Misleading News,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Fake News or Truth? Using Satirical Cues to Detect Potentially Misleading News,

Reference 9

Resolution: verified exact; doi, observed 2026-08-07T11:42:53.800434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9b8af89c-1a02-421e-a645-1fb2409a3d54 · outbound

This paper cites Fake News Detection Through Multi-Perspective Speaker Profiles.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Fake News Detection Through Multi-Perspective Speaker Profiles

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:42:55.322472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 62536efe-233d-42c5-a2d3-437fb45f12b8 · outbound

This paper cites Fake news detection in Urdu language using machine learning,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Fake news detection in Urdu language using machine learning,

Reference 11

Resolution: verified exact; doi, observed 2026-08-07T11:42:53.782213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c861da7f-39c9-49c3-8d9e-20cc1e3439b4 · outbound

This paper cites an unresolved cited work.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:42:55.305094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a8ea799-01c8-49cb-997d-dbfbb63dd6bf · outbound

This paper cites & Daud, A.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings & Daud, A

Reference 13

Resolution: verified exact; doi, observed 2026-08-07T11:42:53.763175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 643eddaf-dac5-47c3-9f3b-7e5ffce3b66c · outbound

This paper cites Deciphering Deception: Unmask- ing Fake News in Multilingual Contexts,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Deciphering Deception: Unmask- ing Fake News in Multilingual Contexts,

Reference 14

Resolution: verified exact; raw_fallback, observed 2026-08-07T11:42:54.834917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation db6f6d2c-ba96-44ec-92cd-b85082de828d · outbound

This paper cites an unresolved cited work.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:42:55.287602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d7d7e40d-33e7-465e-88dc-8eda114db05a · outbound

This paper cites an unresolved cited work.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:42:55.271079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 64884088-c9e3-4b25-b33a-8cd88453a7e3 · outbound

This paper cites Fake News Identifica- tion in Urdu Tweets Using Machine Learning Models,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Fake News Identifica- tion in Urdu Tweets Using Machine Learning Models,

Reference 17

Resolution: verified exact; doi, observed 2026-08-07T11:42:53.742429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 16167b3b-cf8a-4d2a-8482-7384600c893e · outbound

This paper cites Enriching Urdu NER with BERT Embedding, Data Augmentation, and Hybrid Encoder- CNN Architecture,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Enriching Urdu NER with BERT Embedding, Data Augmentation, and Hybrid Encoder- CNN Architecture,

Reference 18

Resolution: verified exact; doi, observed 2026-08-07T11:42:53.722843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 212b9eab-20d7-4818-99da-c0f7a8db0338 · outbound

This paper cites Benchmark Performance of Machine And Deep Learning Based Methodologies for Urdu Text Document Classification.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Benchmark Performance of Machine And Deep Learning Based Methodologies for Urdu Text Document Classification

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:42:55.251506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7a07252b-5d79-489c-a081-f6b5a70226f7 · outbound

This paper cites an unresolved cited work.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:42:55.234517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2094fe6c-534a-4a53-b6fa-309998941a32 · outbound

This paper cites Urdu Fake News Detection Using Ensemble of Machine Learning Models.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Urdu Fake News Detection Using Ensemble of Machine Learning Models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:42:55.216835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f61b7027-e87b-4652-ba4e-bbcc27ad1bf4 · outbound

This paper cites Arabic Fake News Detection in Social Media Context Using Word Embeddings and Pre-trained Transformers,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Arabic Fake News Detection in Social Media Context Using Word Embeddings and Pre-trained Transformers,

Reference 22

Resolution: malformed identifier; doi_truncated, observed 2026-08-07T11:42:53.705163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a430956-1eda-4c73-b077-65a6bae7f5c9 · outbound

This paper cites B., & Ibor, A.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings B., & Ibor, A

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:42:55.198853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 555a9be0-fd9c-43e4-99fa-9040309a9523 · outbound

This paper cites BiL-FaND: leveraging ensemble tech- nique for efficient bilingual fake news detection,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings BiL-FaND: leveraging ensemble tech- nique for efficient bilingual fake news detection,

Reference 24

Resolution: verified exact; doi, observed 2026-08-07T11:42:53.687578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1420afee-49ee-4dc6-8ab0-add3de150144 · outbound

This paper cites Meeting the challenge: A benchmark corpus for automated Urdu meeting summarization,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Meeting the challenge: A benchmark corpus for automated Urdu meeting summarization,

Reference 25

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T11:42:54.730799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e82e78f4-7712-48a4-910a-2d48f0a85d4c · outbound

This paper cites Detection of vio- lence incitation expressions in Urdu tweets using convolutional neural network,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Detection of vio- lence incitation expressions in Urdu tweets using convolutional neural network,

Reference 26

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T11:42:54.627042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d1621883-33dd-4fda-89b9-3e1fb89601a0 · outbound

This paper cites Hate Speech Detection in Roman Urdu using Machine Learning Techniques,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Hate Speech Detection in Roman Urdu using Machine Learning Techniques,

Reference 27

Resolution: verified exact; raw_fallback, observed 2026-08-07T11:42:54.537846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6f6dcb66-014c-434a-9352-0f36c21397a2 · outbound

This paper cites Massively Multilingual Corpus of Sentiment Datasets and Multi-faceted Sentiment Classification Benchmark.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Massively Multilingual Corpus of Sentiment Datasets and Multi-faceted Sentiment Classification Benchmark

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:42:55.182239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3f5ff02d-b7b2-40ad-a801-3952ad66fd41 · outbound

This paper cites Detection of Sarcasm in Urdu Tweets Using Deep Learning and Transformer Based Hybrid Approaches,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Detection of Sarcasm in Urdu Tweets Using Deep Learning and Transformer Based Hybrid Approaches,

Reference 29

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T11:42:54.439308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5d8b818b-1f37-4c41-bbdb-a23f4cdd585c · outbound

This paper cites On the transferability of pre-trained language models for low-resource programming languages,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings On the transferability of pre-trained language models for low-resource programming languages,

Reference 30

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T11:42:54.334603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a35a291e-e08d-4b93-a9d3-cc41e2f1d97f · outbound

This paper cites Fake news detection in low-resource languages: A novel hybrid summarization approach,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Fake news detection in low-resource languages: A novel hybrid summarization approach,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T11:42:53.567133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b765bd62-7907-4fda-a2a7-a9d536c6a0fc · outbound

This paper cites Contextual Embeddings based on Fine-tuned Urdu-BERT for Urdu threatening content and target identification,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Contextual Embeddings based on Fine-tuned Urdu-BERT for Urdu threatening content and target identification,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T11:42:53.573158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9462e97b-ed09-4a3b-8c09-2f42054b62a3 · outbound

This paper cites Toward the Development of Large-Scale Word Embedding for Low- Resourced Language,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Toward the Development of Large-Scale Word Embedding for Low- Resourced Language,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T11:42:53.578398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1848652-6f0d-4c39-95f4-119c75315618 · outbound

This paper cites Multi-class sentiment analysis of urdu text using multilingual BERT,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Multi-class sentiment analysis of urdu text using multilingual BERT,

Reference 34

Resolution: verified exact; doi, observed 2026-08-07T11:42:53.670799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation eee82c5d-f78e-471d-ac3b-e312c40ce46e · outbound

This paper cites UQA: Corpus for Urdu Question Answering.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings UQA: Corpus for Urdu Question Answering

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:42:55.164169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2bb6f5f4-b4b0-4960-81b2-c84f35739a0c · outbound

This paper cites Ontology-Based News Linking for Semantic Tem- poral Queries,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Ontology-Based News Linking for Semantic Tem- poral Queries,

Reference 36

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T11:42:54.000777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6524e095-6441-44a1-b7af-087ce7f01ab7 · outbound

This paper cites Depression Detection Based on Hybrid Deep Learning SSCL Framework Using Self-Attention Mechanism,.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Depression Detection Based on Hybrid Deep Learning SSCL Framework Using Self-Attention Mechanism,

Reference 37

Resolution: verified exact; doi, observed 2026-08-07T11:42:53.649876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1b4f5fc0-b966-4dc3-b202-f0c0b598250c · outbound

This paper cites an unresolved cited work.

Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:42:55.145371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation 7799e91f-c0e5-4405-9709-78c82a8f733b · inbound

DeBERTa-Sentinel: Toward Transparent and Trustworthy Detection of AI-Generated Text cites this paper.

DeBERTa-Sentinel: Toward Transparent and Trustworthy Detection of AI-Generated Text Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-06T00:39:45.396504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.