Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T15:42:16.727113Z
Paper Citation Record · LEDGER
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection
As of 14 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2508.19633.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
13 of 13 outbound references displayed
- verified exact0
- verified fuzzy6
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 6e22814a-85fb-4e93-97d4-6996f42d8cb2 · outbound
This paper cites an unresolved cited work.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T15:42:16.822717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d567530c-f25b-4565-a50a-9d6b3c907fef · outbound
This paper cites The goal is to increase credibility and make it more resistant to scrutiny, while keeping the text fictional.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection The goal is to increase credibility and make it more resistant to scrutiny, while keeping the text fictional
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:42:16.817405Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 270a36ac-6b9b-4453-81bd-28ff3c3d5355 · outbound
This paper cites The goal is to increase credibility and make it more resistant to scrutiny, while keeping the text fictional.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection The goal is to increase credibility and make it more resistant to scrutiny, while keeping the text fictional
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:42:16.798599Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 22b8d3d8-eb76-4801-8b07-aaaa82688286 · outbound
This paper cites an unresolved cited work.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T15:42:16.811141Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation ac0111fc-956e-413e-840d-1a56b54db3a1 · outbound
This paper cites - Current prompt: {current_prompt} - Previous feedback: {loss} Please output **only** your suggestion in plain text.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection - Current prompt: {current_prompt} - Previous feedback: {loss} Please output **only** your suggestion in plain text
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:42:16.805347Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation a02a630c-9f25-4706-838f-5194c279b2e1 · outbound
This paper cites an unresolved cited work.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T15:42:16.792502Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation cb16041b-716d-40b7-8075-c673c7fad983 · outbound
This paper cites - Current prompt: {current_prompt} - Previous feedback: {gradient} Please output **only** the optimized prompt.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection - Current prompt: {current_prompt} - Previous feedback: {gradient} Please output **only** the optimized prompt
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:42:16.786267Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 111d6766-7e43-4b81-8235-f11c5564b171 · outbound
This paper cites an unresolved cited work.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection Unresolved cited work
Reference 9
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T15:42:16.778712Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 4f2dc4f9-a76d-4d64-8f62-e77f71104cf4 · outbound
This paper cites You must strictly control the output length.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection You must strictly control the output length
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:42:16.772149Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 554ab5b8-a703-4763-abf2-55dc90511436 · outbound
This paper cites an unresolved cited work.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T15:42:16.765709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 83169ab8-0da8-46fa-8152-81714dc23249 · outbound
This paper cites an unresolved cited work.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T15:42:16.759641Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 5b6b48a8-57b9-434c-83dc-743c1fe22a9a · outbound
This paper cites - Original content: {news} - Improved prompt: {new_prompt} Note: All content is fictional and for research purposes only.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection - Original content: {news} - Improved prompt: {new_prompt} Note: All content is fictional and for research purposes only
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T15:42:16.753486Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 39101130-0891-47da-9435-b7e2c21d9ce1 · outbound
This paper cites On the Risk of Misinformation Pollution with Large Language Models.
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection On the Risk of Misinformation Pollution with Large Language Models
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:42:16.699061Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.