Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Defending Against Neural Fake News
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:1905.12616.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:42:08.086829Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T17:34:57.491104Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 72101c75-c640-4643-afa0-fee0815a087f · inbound
RoBERTa: A Robustly Optimized BERT Pretraining Approach cites this paper.
RoBERTa: A Robustly Optimized BERT Pretraining Approach Defending Against Neural Fake News
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T04:47:44.510678Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation a3d9bcf7-92b2-42ab-a219-9d30cd7834e4 · inbound
CTRL: A Conditional Transformer Language Model for Controllable Generation cites this paper.
CTRL: A Conditional Transformer Language Model for Controllable Generation Defending Against Neural Fake News
Reference 52
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T06:14:02.584681Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation ef5858c0-3f2a-4b7d-ae2b-5c2f722ede88 · inbound
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism cites this paper.
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism Defending Against Neural Fake News
Reference 36
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T18:34:44.893015Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 4dba69d6-dbf4-4bc5-b841-39a2cb1f2ac2 · inbound
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer cites this paper.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Defending Against Neural Fake News
Reference 81
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T05:37:55.443443Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 17e0647c-09c0-4cf2-bcdb-6d709d2c31a2 · inbound
Compressive Transformers for Long-Range Sequence Modelling cites this paper.
Compressive Transformers for Long-Range Sequence Modelling Defending Against Neural Fake News
Reference 134
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-18T10:46:16.642228Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation c84aeb14-4740-4983-af08-2daf202ba0fd · inbound
Language Models are Few-Shot Learners cites this paper.
Language Models are Few-Shot Learners Defending Against Neural Fake News
Reference 84
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T12:05:38.120965Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 84723f2a-e0c0-4656-8f39-e7efcff07958 · inbound
Deduplicating Training Data Makes Language Models Better cites this paper.
Deduplicating Training Data Makes Language Models Better Defending Against Neural Fake News
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T13:39:31.671660Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 41f90178-98a2-4fef-8b57-31015b5cf302 · inbound
Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model cites this paper.
Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model Defending Against Neural Fake News
Reference 77
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T12:14:26.707955Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2b39f71e-71ad-40f3-986d-520bbfb85496 · inbound
OPT: Open Pre-trained Transformer Language Models cites this paper.
OPT: Open Pre-trained Transformer Language Models Defending Against Neural Fake News
Reference 52
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T20:53:17.352441Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8ff54ae3-b613-4b61-8145-ee5cf5a4f6c7 · inbound
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews cites this paper.
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews Defending Against Neural Fake News
Reference 14
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-24T02:48:47.452111Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2908c32e-0c96-4f04-8231-2df73864a7c9 · inbound
Transforming Chatbot Text: A Sequence-to-Sequence Approach cites this paper.
Transforming Chatbot Text: A Sequence-to-Sequence Approach Defending Against Neural Fake News
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:42:08.086829Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c9573cde-528c-424d-96de-ba79c9f2c269 · inbound
ISACL: Internal State Analyzer for Copyrighted Training Data Leakage cites this paper.
ISACL: Internal State Analyzer for Copyrighted Training Data Leakage Defending Against Neural Fake News
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T16:50:28.281644Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b86c0ef7-0e0c-49e0-932f-620836b9025c · inbound
A Comprehensive Dataset for Human vs. AI Generated Text Detection cites this paper.
A Comprehensive Dataset for Human vs. AI Generated Text Detection Defending Against Neural Fake News
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T08:03:26.485271Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e6460ca2-cc2a-4857-b95f-5fbddd6fe8ce · inbound
Findings of the Counter Turing Test: AI-Generated Text Detection cites this paper.
Findings of the Counter Turing Test: AI-Generated Text Detection Defending Against Neural Fake News
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T05:29:39.559887Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 0569f8c8-630b-4964-b171-f58ffcb9ddd8 · inbound
Findings of the Counter Turing Test: AI-Generated Text Detection cites this paper.
Findings of the Counter Turing Test: AI-Generated Text Detection Defending Against Neural Fake News
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T17:34:57.495045Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.