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Paper Citation Record · LEDGER

Fake News Detection After LLM Laundering: Measurement and Explanation

As of 19 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 2 inbound Pith citation observations for arXiv:2501.18649.

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

pith.paper-citation-record.v1
2501.18649 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T04:36:03.887694Z

measured 71 of 71 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:31:54.478102Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:31:58.784964Z

Reference resolution

69 of 69 outbound references displayed

  • verified exact10
  • verified fuzzy42
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3229cac3-83a1-4486-8ec2-ebbe13a78290 · outbound

This paper cites Joint copying and restricted gener- ation for paraphrase.

Fake News Detection After LLM Laundering: Measurement and Explanation Joint copying and restricted gener- ation for paraphrase

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.709422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.630900Z digest=sha256:1cc6fcd86ba08dd157ec45277e43426bfcaf65c53a925b299eedcf27ba6bc575

Observation c899c07a-b3bc-409d-a2c4-51e126252679 · outbound

This paper cites Semantic parsing via paraphrasing.

Fake News Detection After LLM Laundering: Measurement and Explanation Semantic parsing via paraphrasing

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.698728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.635762Z digest=sha256:fe2f40615599ce2079b890b4b9c0d5c9d52c7aaf39e73fa0f72d6a4f9298d06b

Observation ced3dff4-5999-48ce-b208-fe23d1bcf0f7 · outbound

This paper cites Open question answering over curated and extracted knowledge bases.

Fake News Detection After LLM Laundering: Measurement and Explanation Open question answering over curated and extracted knowledge bases

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.687817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.640051Z digest=sha256:71af2073b350228f1f9c136770e7266c97048f65feb6c40e0a75fef4e33785ef

Observation d62357fd-724b-475a-9d93-b38a8e50ece5 · outbound

This paper cites Answering questions with complex semantic constraints on open knowledge bases.

Fake News Detection After LLM Laundering: Measurement and Explanation Answering questions with complex semantic constraints on open knowledge bases

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.676470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.644239Z digest=sha256:b2b7be149f7de0fd21444834530376c6c82601893e5b59674efa474f766e0ca4

Observation fa3e4d2b-38a9-476c-beb2-8e358bbe3578 · outbound

This paper cites QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension.

Fake News Detection After LLM Laundering: Measurement and Explanation QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.648385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.648385Z digest=sha256:2585fd03ea4dbb6e710a8ca60548627f22f26fda6d26a63bd31fa975b94ce282

Observation bd92657d-f727-49e4-af25-c9a8efbcfa58 · outbound

This paper cites Adversarial Example Generation with Syntactically Controlled Paraphrase Networks.

Fake News Detection After LLM Laundering: Measurement and Explanation Adversarial Example Generation with Syntactically Controlled Paraphrase Networks

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.653239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.653239Z digest=sha256:ee327519599ead93b32625c2ae60981a667b9e03e235c65e7cadd1c8f63956d2

Observation 257b4649-2d95-40cb-a1f4-2b300fb920be · outbound

This paper cites Natural language pro- cessing: state of the art, current trends and challenges.

Fake News Detection After LLM Laundering: Measurement and Explanation Natural language pro- cessing: state of the art, current trends and challenges

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.665134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.657753Z digest=sha256:0001c9107d926f045181ef086b7de6a8c91fc3f53c0c2ffd10f875f202a7d5ad

Observation be233d8c-c0b0-4666-b85e-bb49376145aa · outbound

This paper cites Openai report details election interference efforts, hoaxes.

Fake News Detection After LLM Laundering: Measurement and Explanation Openai report details election interference efforts, hoaxes

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.653655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.661511Z digest=sha256:eb6858e67fc9705c3837fb89effc958a7040e6802fe05968b9b8a14860f954b0

Observation 08b60108-49b9-4354-a06c-c51d9aeeb4b5 · outbound

This paper cites Language models are few-shot learners.

Fake News Detection After LLM Laundering: Measurement and Explanation Language models are few-shot learners

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.642586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.665296Z digest=sha256:38665e046ca4d869bae4a972f1675ddd3b1cfcd4e5912119ccbb07ad36e8b11f

Observation 872d9e2e-1a8d-458e-90a1-b93217c5f5c4 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Fake News Detection After LLM Laundering: Measurement and Explanation BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.669794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.669794Z digest=sha256:d34945e29fc304d9c13701263a63c6e74915af96e3aae4e73a7eed45c475f2be

Observation 70fd48be-1181-4c7c-811c-bf65c5da0580 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

Fake News Detection After LLM Laundering: Measurement and Explanation Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.631474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.673995Z digest=sha256:9fa37d0df2aa77db5eb8914feb044b59319c15aa122cff2140cd1141b91c1015

Observation 3b40f05f-f959-4a4e-b58e-8002884cca58 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Fake News Detection After LLM Laundering: Measurement and Explanation LLaMA: Open and Efficient Foundation Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.677824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.677824Z digest=sha256:27b2de08354c204c00f0a68fc83fde683297fedc9ee3feb64320b04019041b49

Observation 4f419194-8f5f-4470-aeea-11ae4f9ffcfd · outbound

This paper cites Defending against neural fake news.

Fake News Detection After LLM Laundering: Measurement and Explanation Defending against neural fake news

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.619655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.681712Z digest=sha256:30cd3263af459c8205a7f191f8e30cb43c3094ec2eeb9b183e3c89bd28251d8d

Observation d7c99a07-06f8-43d0-912b-f7af75912c86 · outbound

This paper cites Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data Generation.

Fake News Detection After LLM Laundering: Measurement and Explanation Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data Generation

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:36:04.209542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.685348Z digest=sha256:73f0b535ce5cb74996be28255fd5bc4f99410a9ccd6d770a9d620fe83c748f16

Observation f5beb339-04e4-49b8-8ac0-1059c759aecf · outbound

This paper cites Can LLM-Generated Misinformation Be Detected?.

Fake News Detection After LLM Laundering: Measurement and Explanation Can LLM-Generated Misinformation Be Detected?

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.689428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.689428Z digest=sha256:74059045344f957fce4f2d47c8a4f18ec90326b5238fe9282a4339c3d314f490

Observation 8963af17-4586-4b34-be0f-04c86f749cea · outbound

This paper cites Fake News Detectors are Biased against Texts Generated by Large Language Models.

Fake News Detection After LLM Laundering: Measurement and Explanation Fake News Detectors are Biased against Texts Generated by Large Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.693285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.693285Z digest=sha256:c4d7d4f7dd346d5adc3aa1ed3fd1c2a96a0446f5f1950e9eb0f266d510f7c766

Observation 491946a5-09f9-4afe-ac8f-58f375015412 · outbound

This paper cites The efficacy of detecting ai- generated fake news using transfer learning.

Fake News Detection After LLM Laundering: Measurement and Explanation The efficacy of detecting ai- generated fake news using transfer learning

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.608828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.696769Z digest=sha256:3b2b31515e5579471b41d4ce4efb0e495fcc215b6ff92ec3958f3859f9a6f04c

Observation 9f5b7891-df67-47a9-b650-d16f213ecf03 · outbound

This paper cites Disinformation Detection: An Evolving Challenge in the Age of LLMs.

Fake News Detection After LLM Laundering: Measurement and Explanation Disinformation Detection: An Evolving Challenge in the Age of LLMs

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:36:04.172481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.700613Z digest=sha256:e4ed6e9dda1b83c9d24e7d75066eb3a9513782e02240d87df36135ee47df17db

Observation 52912d1c-676f-4bbb-be1c-d1f7be557b3e · outbound

This paper cites Bleu: a method for auto- matic evaluation of machine translation.

Fake News Detection After LLM Laundering: Measurement and Explanation Bleu: a method for auto- matic evaluation of machine translation

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.598784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.704229Z digest=sha256:f6d67f4fa1903fa83b912fb251acfe00e1c4c0e5b3e748945a8d3f217d9ac376

Observation 2b37b090-be87-4496-83c6-a77bbc4c13c2 · outbound

This paper cites Rouge: A package for auto- matic evaluation of summaries.

Fake News Detection After LLM Laundering: Measurement and Explanation Rouge: A package for auto- matic evaluation of summaries

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.588160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.707845Z digest=sha256:f30b57855859a47f88ca1d309abecd48f33adb2407f212cb590dd7de98a4174b

Observation f1ff0001-82af-4be5-ab92-62a2dd0c2119 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

Fake News Detection After LLM Laundering: Measurement and Explanation BERTScore: Evaluating Text Generation with BERT

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.711414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.711414Z digest=sha256:07ec72e66235b51949e12540f3d8af40dde1dcb02f92f23c7ea565fbfcc51705

Observation 66bd624d-07a2-4241-90a2-7fb6a9e27d54 · outbound

This paper cites A study of translation edit rate with targeted hu- man annotation.

Fake News Detection After LLM Laundering: Measurement and Explanation A study of translation edit rate with targeted hu- man annotation

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.576746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.715292Z digest=sha256:420507ad797ce7cfc4299502015c7e33bd21193f9aa9427806ea1e7d68b89bf6

Observation 19bd7c01-700c-4eaa-9f73-4e50437f860d · outbound

This paper cites A survey on evaluation metrics for machine translation.

Fake News Detection After LLM Laundering: Measurement and Explanation A survey on evaluation metrics for machine translation

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.565693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.719096Z digest=sha256:9bbad6eb7bdd78a968009a915e782c4ca396df72d01ae92e7a6eb3b0f16c6b8d

Observation 775c714b-9bba-45f7-91df-0205d8f85a6b · outbound

This paper cites Meant 2.0: Accurate semantic mt evaluation for any output language.

Fake News Detection After LLM Laundering: Measurement and Explanation Meant 2.0: Accurate semantic mt evaluation for any output language

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.554271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.722326Z digest=sha256:bf02df308a78c03c2b4d948175d1b80f24145cf36cf847535044116ed737c18a

Observation 220c7ba5-d764-4a45-ac51-c98b66955a49 · outbound

This paper cites Paraphrasing questions using given and new information.

Fake News Detection After LLM Laundering: Measurement and Explanation Paraphrasing questions using given and new information

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.542759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.725953Z digest=sha256:f5542f4d016fc203e9ccc84136ce9cee41cfe8d4602b1625a079bd0937213eb6

Observation cc365db6-d1b4-45d6-9129-d7d3b984e6b7 · outbound

This paper cites Unt: Sub- finder: Combining knowledge sources for au- tomatic lexical substitution.

Fake News Detection After LLM Laundering: Measurement and Explanation Unt: Sub- finder: Combining knowledge sources for au- tomatic lexical substitution

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.531817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.729604Z digest=sha256:98259d41e9a1c0d402755a9ecd3da8655a8c36f5ea32749ad6f1059488e407f1

Observation d2797626-08a5-4d8e-a76e-385bc6010fef · outbound

This paper cites Paraphrase Generation with Deep Reinforcement Learning.

Fake News Detection After LLM Laundering: Measurement and Explanation Paraphrase Generation with Deep Reinforcement Learning

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:36:04.147016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.732849Z digest=sha256:9fe08b8a00ef6e5ed6410f706bdbd5839aad019d9d79979b837c5d094782e812

Observation a3259b9b-0799-47d9-81ad-b63de9fad3cb · outbound

This paper cites A deep generative framework for paraphrase generation.

Fake News Detection After LLM Laundering: Measurement and Explanation A deep generative framework for paraphrase generation

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.521323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.736495Z digest=sha256:4da5413ca4a72a8394debbf112ebca3f1cf3f1e8d29f17946eee49a6e5d652e2

Observation c15d5134-d7a1-4484-89da-f633578a5d71 · outbound

This paper cites Unsupervised Paraphrase Generation using Pre-trained Language Models.

Fake News Detection After LLM Laundering: Measurement and Explanation Unsupervised Paraphrase Generation using Pre-trained Language Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.739973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.739973Z digest=sha256:cd7c137bdcdb28badaf994a7908a5821053b725f64bce1685e068e7cadaabd9f

Observation d3bcbb30-3db2-4392-80c7-865886d923a8 · outbound

This paper cites Neural Paraphrase Generation with Stacked Residual LSTM Networks.

Fake News Detection After LLM Laundering: Measurement and Explanation Neural Paraphrase Generation with Stacked Residual LSTM Networks

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.743748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.743748Z digest=sha256:02136b9cfd6b192cc3d58e66881f7911f38fb865b79be4411e2134c01cb287c5

Observation 18e4ed5b-69e6-4e1c-9f3d-62604afea453 · outbound

This paper cites Deep residual learning for image recognition.

Fake News Detection After LLM Laundering: Measurement and Explanation Deep residual learning for image recognition

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.510848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.747470Z digest=sha256:555bf332f3658bb1532ff189f59a2ec37f224c76a82277a2bb50e9828a64917f

Observation 97bd1dd3-6d79-43bc-acb0-ea06b9d2bfba · outbound

This paper cites Paraphrase generation with latent bag of words.

Fake News Detection After LLM Laundering: Measurement and Explanation Paraphrase generation with latent bag of words

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.500596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.751054Z digest=sha256:026c33859a0f44220527c751250777c2c7098601ef3db1b9dbb5c50044da6227

Observation 875692cf-0c0b-45af-ba87-c9c2751e39bc · outbound

This paper cites Neural Syntactic Preordering for Controlled Paraphrase Generation.

Fake News Detection After LLM Laundering: Measurement and Explanation Neural Syntactic Preordering for Controlled Paraphrase Generation

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:36:04.112610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.754656Z digest=sha256:e73bde81ef3610f8cbf030148c7b6a12d6d72cf4733569ae27ce3b6b9f66c39a

Observation 4f057b8d-94f8-4c36-8e65-27b819ef2883 · outbound

This paper cites Decomposable Neural Paraphrase Generation.

Fake News Detection After LLM Laundering: Measurement and Explanation Decomposable Neural Paraphrase Generation

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:36:04.097966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.758853Z digest=sha256:ba64bec2c16f7a6f19398cfde2f6f6160556bf6b6141dbb0e834575a07f4f09c

Observation 2d7ded58-96ce-4f0c-b1bb-40d438c96301 · outbound

This paper cites Generate rather than Retrieve: Large Language Models are Strong Context Generators.

Fake News Detection After LLM Laundering: Measurement and Explanation Generate rather than Retrieve: Large Language Models are Strong Context Generators

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.762922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.762922Z digest=sha256:ebb1202294491efd4e2d90c9dbba021c05750344e60d644b9115745915d4049f

Observation df5dd7a0-271d-4696-8748-9f6a751b666a · outbound

This paper cites Paraphrasing with Large Language Models.

Fake News Detection After LLM Laundering: Measurement and Explanation Paraphrasing with Large Language Models

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:36:04.071257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.766986Z digest=sha256:88a40568fdc9ed2fe12c1d3b52fbbb679979f802b3b6f96f5420332be4f3ed5c

Observation 8633e30c-48ce-4122-81be-b856a271b028 · outbound

This paper cites How Large Language Models are Transforming Machine-Paraphrased Plagiarism.

Fake News Detection After LLM Laundering: Measurement and Explanation How Large Language Models are Transforming Machine-Paraphrased Plagiarism

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:36:04.055016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.770782Z digest=sha256:b700f6741ec0bbb08624f72edd3e8544f8692d075d787638f65ec772f2f317b0

Observation 7f1dd8b1-dddb-4b88-bd95-3c2f10cdca87 · outbound

This paper cites Pag-llm: Paraphrase and aggregate with large language models for minimizing intent clas- sification errors.

Fake News Detection After LLM Laundering: Measurement and Explanation Pag-llm: Paraphrase and aggregate with large language models for minimizing intent clas- sification errors

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.490354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.774976Z digest=sha256:30ee14f73d59aa80f05e74f61e9134a922bd9441e3adb41c050fda922f863bd6

Observation 0db5a29b-82ce-4f8e-9700-3b8397c6f31b · outbound

This paper cites TinyBERT: Distilling BERT for Natural Language Understanding.

Fake News Detection After LLM Laundering: Measurement and Explanation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.779140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.779140Z digest=sha256:f93055b5d3abf8b3d3ddc1e9807594485926740edb22acf4da54f9a91f9bb390

Observation c035d37f-120b-45e6-a047-ebe431717166 · outbound

This paper cites Investigating paraphrasing-based data augmentation for task- oriented dialogue systems.

Fake News Detection After LLM Laundering: Measurement and Explanation Investigating paraphrasing-based data augmentation for task- oriented dialogue systems

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.479646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.783128Z digest=sha256:8b5b8d0aa35c574991d6bcd15aae7512c6b4255297b78a06e75012ab4892db69

Observation 2ae586ba-3d5f-4ad6-9248-f61213b1f447 · outbound

This paper cites Submodular optimization-based diverse paraphrasing and its effectiveness in data augmentation.

Fake News Detection After LLM Laundering: Measurement and Explanation Submodular optimization-based diverse paraphrasing and its effectiveness in data augmentation

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.468973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.786681Z digest=sha256:bbf6b76676667085b22f9cdf83403ef861619e454dabaf4d9b3eff635fe7dfaf

Observation 032ad6e4-0385-44e2-adc5-2e925aa64139 · outbound

This paper cites Improving data augmentation for low resource speech-to-text translation with diverse para- phrasing.

Fake News Detection After LLM Laundering: Measurement and Explanation Improving data augmentation for low resource speech-to-text translation with diverse para- phrasing

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.458185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.790468Z digest=sha256:bd458fb383f3ff468ddfde6e37b1c98836519d1b92d7fb807530c3d6d202c103

Observation bd1eeca0-680b-4d3f-87ed-da8c5840907f · outbound

This paper cites T5w: A paraphras- ing approach to oversampling for imbalanced text classification.

Fake News Detection After LLM Laundering: Measurement and Explanation T5w: A paraphras- ing approach to oversampling for imbalanced text classification

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.447662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.794149Z digest=sha256:cbc8dc0779870ab5ff898b40d298be39d7ee18fa4efb3e70ef3ee02d130d7e53

Observation 74e4b7c2-d698-4ac9-97d3-b6ca5f7fff81 · outbound

This paper cites ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations.

Fake News Detection After LLM Laundering: Measurement and Explanation ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.797878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.797878Z digest=sha256:f122beff43d5f304490dbbd71bf0f16882dc717c1f1fca1ebc0ee995dea5791f

Observation 48c830ac-f7f7-4057-813c-923992222cf0 · outbound

This paper cites Automatically constructing a corpus of sentential paraphrases.

Fake News Detection After LLM Laundering: Measurement and Explanation Automatically constructing a corpus of sentential paraphrases

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.436612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.801687Z digest=sha256:f884643120238528b2ae5db11a29855264c2913985a93852d6d3ca81bf2be059

Observation 029f22a9-ceac-4fb8-b366-4d909cb41ff2 · outbound

This paper cites Ppdb: The paraphrase database.

Fake News Detection After LLM Laundering: Measurement and Explanation Ppdb: The paraphrase database

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.425927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.805153Z digest=sha256:d797800074c4cfcee27de5c2914137cb48bb134f0b9bb0576ac828b1af251945

Observation 47e3880f-2f60-46eb-833b-c849edc56c24 · outbound

This paper cites ParaSCI: A Large Scientific Paraphrase Dataset for Longer Paraphrase Generation.

Fake News Detection After LLM Laundering: Measurement and Explanation ParaSCI: A Large Scientific Paraphrase Dataset for Longer Paraphrase Generation

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:36:04.015722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.808505Z digest=sha256:e7515e513a4d5dfc8877eab7d9c2633b0500eff04ec855e52058281faa147af5

Observation aeddceb0-ddf1-4b3f-8352-154d3a99692a · outbound

This paper cites Gathering and generating paraphrases from twitter with application to normalization.

Fake News Detection After LLM Laundering: Measurement and Explanation Gathering and generating paraphrases from twitter with application to normalization

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.415944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.812347Z digest=sha256:04b11fad155cbadd7a8616726b8af45f2795f4817fca15d82556899ccab9e3bb

Observation 5f5b9f89-35d8-4034-a5a4-ff491d155dc3 · outbound

This paper cites Cgmh: Constrained sentence generation by metropolis-hastings sampling.

Fake News Detection After LLM Laundering: Measurement and Explanation Cgmh: Constrained sentence generation by metropolis-hastings sampling

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.405884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.815842Z digest=sha256:6d622602681454e103fea7701aeb3bc4bac46e4553e7eeecb5a953cd75f916db

Observation f9cffe65-87ab-459c-89a7-7977d6e56505 · outbound

This paper cites EUCA: the End-User-Centered Explainable AI Framework.

Fake News Detection After LLM Laundering: Measurement and Explanation EUCA: the End-User-Centered Explainable AI Framework

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.819464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.819464Z digest=sha256:6f0180e54d005eb8c58dcf5d1209aaab254327a5fba2bb40162c8ef4777a5bac

Observation 7a576beb-6e89-4c48-b231-01b80a86a614 · outbound

This paper cites why should i trust you?.

Fake News Detection After LLM Laundering: Measurement and Explanation why should i trust you?

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.395219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.823122Z digest=sha256:6b378b617e3eb950f442a6fb844ea6528c5ff0b64f5aa75ede9c5386d3a91d88

Observation 65baeea7-1af0-49c9-949b-48593e135c79 · outbound

This paper cites New explainability method for bert- based model in fake news detection.

Fake News Detection After LLM Laundering: Measurement and Explanation New explainability method for bert- based model in fake news detection

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.385567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.826446Z digest=sha256:8484cf309cd2a89d609335ddbbe647d932bd806223a8c01f8671d56f410bfec8

Observation b44e953d-8c1a-4a6c-967c-61e53b1a5aac · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

Fake News Detection After LLM Laundering: Measurement and Explanation A Unified Approach to Interpreting Model Predictions

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.830190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.830190Z digest=sha256:f435c2852e90d4c037cef18b5c5c9fe33b4c9113c8d5c3cc8f976def81c01c15

Observation f3108aef-37c4-4b3d-8b33-9048d142e887 · outbound

This paper cites Combat covid-19 infodemic using explainable natural language processing models.

Fake News Detection After LLM Laundering: Measurement and Explanation Combat covid-19 infodemic using explainable natural language processing models

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.374737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.834114Z digest=sha256:27fa00975f77b5381bf646c58b7a9024518b8c058c8d8c7fe66f39fe5fb51b67

Observation aa21e311-3f4b-48e8-add9-331a56a51242 · outbound

This paper cites Explainable machine learning for fake news detection.

Fake News Detection After LLM Laundering: Measurement and Explanation Explainable machine learning for fake news detection

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.363783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.837763Z digest=sha256:c6b0207111b1716a1aab9ef7f0aea11a8ff1f731fed61fa4d435068415ecaf0e

Observation 07d36183-10f8-420d-83a0-c82f5c74c32c · outbound

This paper cites Axiomatic attribution for deep networks.

Fake News Detection After LLM Laundering: Measurement and Explanation Axiomatic attribution for deep networks

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.353367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.841394Z digest=sha256:1d5536b791c8fe7ffc09c06fb244d4dd1746f1252a33df7504976d61e9e9d974

Observation 216811c8-f8fc-4e2f-8542-76dafdd222fe · outbound

This paper cites Learning important features through propagating activation differences.

Fake News Detection After LLM Laundering: Measurement and Explanation Learning important features through propagating activation differences

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.342575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.844757Z digest=sha256:5ae678eecbac438454de150629e9ea66ec1a71e99d90a768047f27932da14d60

Observation 28dbfb11-88a7-4c61-b73f-a0988d390e60 · outbound

This paper cites A causal framework for explaining the predictions of black-box sequence-to-sequence models.

Fake News Detection After LLM Laundering: Measurement and Explanation A causal framework for explaining the predictions of black-box sequence-to-sequence models

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.848464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.848464Z digest=sha256:65839c3330dbe86247f59f09614adf8fe214aba41b87885f35bd761e901786d7

Observation 2af972d6-6640-4dd7-8544-b329a575f144 · outbound

This paper cites A song of (dis) agree- ment: Evaluating the evaluation of explainable artificial intelligence in natural language pro- cessing.

Fake News Detection After LLM Laundering: Measurement and Explanation A song of (dis) agree- ment: Evaluating the evaluation of explainable artificial intelligence in natural language pro- cessing

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.332073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.852092Z digest=sha256:897e06c9f78a77d187e43980485297f25f430939a87761a911bd4e4ac22fbd4a

Observation bfb0ac97-13d5-476a-bc6b-6e5f7cdf95a6 · outbound

This paper cites Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference.

Fake News Detection After LLM Laundering: Measurement and Explanation Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:36:03.965943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.855616Z digest=sha256:59c11cc4382e63a5194c7949d93fe43de42297cf3c19dfea8068ec8dfc6c8a1e

Observation a59e75d2-60f0-4064-a3af-41f9cb65c191 · outbound

This paper cites Model Explainability in Deep Learning Based Natural Language Processing.

Fake News Detection After LLM Laundering: Measurement and Explanation Model Explainability in Deep Learning Based Natural Language Processing

Reference 61

Resolution
verified exact
local_arxiv, observed 2026-08-10T04:36:03.948443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.859512Z digest=sha256:ee70c90873bbd763fd05a344554a06d08efe3029778b502768a9ccd451f95d0c

Observation f5cc7536-e2e8-4b15-9b7e-ac737bb5058c · outbound

This paper cites Fighting an infodemic: Covid-19 fake news dataset, 2020.

Fake News Detection After LLM Laundering: Measurement and Explanation Fighting an infodemic: Covid-19 fake news dataset, 2020

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.320876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.863201Z digest=sha256:14d9068df655dbd791df5f032086d4fab3d13ead7e2283f272476f60020f1300

Observation c76b9a6f-ed74-4733-ae31-ff03753cfabc · outbound

This paper cites "Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection.

Fake News Detection After LLM Laundering: Measurement and Explanation "Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.866713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.866713Z digest=sha256:d646c104626dd384e64dc9e9216d42e99031e827485b6f06108986afef5572e4

Observation f9757858-e68a-4e5e-9821-21e26c1ae416 · outbound

This paper cites NLTK: The Natural Language Toolkit.

Fake News Detection After LLM Laundering: Measurement and Explanation NLTK: The Natural Language Toolkit

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-10T04:36:03.870317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:36:03.870317Z digest=sha256:b9de3437f1495d4160463ffa2fd17468b613e5477f3d9cfa5c59dbc8912c516e

Observation dac7b74f-3e44-4aaa-b0f3-8ae9f0ced8f8 · outbound

This paper cites A survey on text classification algorithms: From text to predictions.

Fake News Detection After LLM Laundering: Measurement and Explanation A survey on text classification algorithms: From text to predictions

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.308972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.873873Z digest=sha256:f794b8fd5d245192ff9dfd5575d17118155a264f9e84f4c6d9db8b9c50a07e92

Observation 85b60293-f579-4173-9fba-86554da75530 · outbound

This paper cites Pegasus: Pre-training with ex- tracted gap-sentences for abstractive summa- rization.

Fake News Detection After LLM Laundering: Measurement and Explanation Pegasus: Pre-training with ex- tracted gap-sentences for abstractive summa- rization

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.297408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.877631Z digest=sha256:ad6cb2bb52b4e4fd8f4431eabd1994c53d3f9d6100b6899ab3b0cd578827c0c3

Observation e168d7d7-b850-49df-9584-81d7fe5a0927 · outbound

This paper cites Scikit-learn: Machine learning in python.

Fake News Detection After LLM Laundering: Measurement and Explanation Scikit-learn: Machine learning in python

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.285875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.881239Z digest=sha256:3e2f2bb61afbc0b9dd7c364cd0108ac4fa1d7954276279bc6f3e2a26b22a78d1

Observation 8379f330-7d8b-4947-90ac-58ffee859da0 · outbound

This paper cites flan- t5-base-imdb-text-classification.

Fake News Detection After LLM Laundering: Measurement and Explanation flan- t5-base-imdb-text-classification

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.274624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.884361Z digest=sha256:5470e1369af69dd32a37cd59d472a8effa63dbc6094cd354c87c39270b566ba4

Observation 1b27b0df-774b-4a48-9c41-6b19c35feefc · outbound

This paper cites distilbert-base-multilingual- cased-sentiments-student (revision 2e33845), 2023.

Fake News Detection After LLM Laundering: Measurement and Explanation distilbert-base-multilingual- cased-sentiments-student (revision 2e33845), 2023

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T04:36:04.262680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T04:36:03.887694Z digest=sha256:35726833b49b877e3fc5bf087d26660331d63da9f7b8870e23a84f039005c326

Pith citing papers

Observation 507c47e8-3cc7-4c74-9520-1fce2ec8e101 · inbound

Debate-to-Detect: Reformulating Misinformation Detection as a Real-World Debate with Large Language Models cites this paper.

Debate-to-Detect: Reformulating Misinformation Detection as a Real-World Debate with Large Language Models Fake News Detection After LLM Laundering: Measurement and Explanation

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:31:58.858096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T14:31:54.478102Z digest=sha256:b2bb339d8b5003a7d9c5f65047543339680344cd041e852795b9ec0f25ec12eb

Observation ec3568f2-1c39-4b49-8f3e-488aaa49292e · inbound

Large Language Models in Misinformation Ecosystems: Misuse, Defense, and Vulnerability cites this paper.

Large Language Models in Misinformation Ecosystems: Misuse, Defense, and Vulnerability Fake News Detection After LLM Laundering: Measurement and Explanation

Reference 44

Resolution
unresolved
no resolver link, observed 2026-07-14T12:01:22.824663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T12:01:22.824663Z digest=sha256:aab6cac664717f458596c835efa29d093959dfcfa6c4287ca7951a7cb5a02e2a