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Paper Citation Record · LEDGER

Demystifying Prompts in Language Models via Perplexity Estimation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2212.04037.

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

pith.paper-citation-record.v1
2212.04037 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:59:38.244178Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:59:45.002855Z

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 fa491dbd-8986-483e-8de1-53b530d9f23e · inbound

Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting cites this paper.

Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting Demystifying Prompts in Language Models via Perplexity Estimation

Reference 66

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T01:59:51.403617Z

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.

source=arxiv_source observed=2026-05-17T01:59:51.326493Z digest=sha256:bb9e569df90890a0bd759bd6adaf669c8b91b0b4289b1c1db15af065fb97a864

Observation b363b654-5d11-4767-ab56-ffb7ec8526d7 · inbound

CoTSRF: Utilize Chain of Thought as Stealthy and Robust Fingerprint of Large Language Models cites this paper.

CoTSRF: Utilize Chain of Thought as Stealthy and Robust Fingerprint of Large Language Models Demystifying Prompts in Language Models via Perplexity Estimation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T14:59:38.244178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:59:38.244178Z digest=sha256:c24a91caab9868b4dfd0cc8be8222f86aa16eda1b6616f941b71971bb83ad330

Observation 973ecd88-25c3-48d8-bd5d-3f1d2c4e56b4 · inbound

Through the Stealth Lens: Attention-Aware Defenses Against Poisoning in RAG cites this paper.

Through the Stealth Lens: Attention-Aware Defenses Against Poisoning in RAG Demystifying Prompts in Language Models via Perplexity Estimation

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-25T08:15:34.132065Z

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.

source=pdf_text observed=2026-05-25T08:10:31.473565Z digest=sha256:b65f5e7bd5567374baf2e8bd95ea16399d4d3036ffcccd1f68c878ce3f26b468

Observation c0996a94-20ab-416e-bf13-3c7d4809bebc · inbound

Low-Perplexity LLM-Generated Sequences and Where To Find Them cites this paper.

Low-Perplexity LLM-Generated Sequences and Where To Find Them Demystifying Prompts in Language Models via Perplexity Estimation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T20:44:59.061295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:44:59.061295Z digest=sha256:fdd3d603cbf510a31feac4244cf393f4410165aa6baae5b0c26774716daf656b

Observation e677df19-40c9-4493-a1a5-ae63223a43ca · inbound

Optimus: A Robust Defense Framework for Mitigating Toxicity while Fine-Tuning Conversational AI cites this paper.

Optimus: A Robust Defense Framework for Mitigating Toxicity while Fine-Tuning Conversational AI Demystifying Prompts in Language Models via Perplexity Estimation

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-22T12:21:31.178964Z

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.

source=pdf_text observed=2026-05-22T12:17:59.458633Z digest=sha256:736b32ca9129e3915bc21e77bbf7c328233974a72152a7e0bc029bc439dffe24

Observation 1464b78d-3bcb-46c2-993a-bcfe979dc1b1 · inbound

Unveiling Effective In-Context Configurations for Image Captioning: An External & Internal Analysis cites this paper.

Unveiling Effective In-Context Configurations for Image Captioning: An External & Internal Analysis Demystifying Prompts in Language Models via Perplexity Estimation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T19:21:13.301322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:21:13.301322Z digest=sha256:e941491d3efbd30d0a793b57693bdf008f7a36c9ffc7950fd2e9d3a1e50bbf59

Observation 022ea7e1-57c9-406b-b3b9-d06691611424 · inbound

How Important is `Perfect' English for Machine Translation Prompts? cites this paper.

How Important is `Perfect' English for Machine Translation Prompts? Demystifying Prompts in Language Models via Perplexity Estimation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T17:56:59.267584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:56:59.267584Z digest=sha256:92210a3778de3f549aa44013b37ca2a466d12e302048e2a9fabc452f83f6d9d7

Observation 5cc7940e-03c1-4de9-9134-c38381fea81f · inbound

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques cites this paper.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Demystifying Prompts in Language Models via Perplexity Estimation

Reference 195

Resolution
unresolved
no resolver link, observed 2026-08-06T16:24:30.557566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:24:30.557566Z digest=sha256:c79c260343f333eec1119ea1b016679ad200aa71f9c61327add931451b4b432a

Observation 2ddd3a27-8f74-448f-a245-d26af26970d0 · inbound

DICE: Dynamic In-Context Example Selection in LLM Agents via Efficient Knowledge Transfer cites this paper.

DICE: Dynamic In-Context Example Selection in LLM Agents via Efficient Knowledge Transfer Demystifying Prompts in Language Models via Perplexity Estimation

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T10:43:45.719310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:43:45.719310Z digest=sha256:1bc736ed0edfc10492fec51ea4cfa0e6ab22eeca57fa71488a385207b4ff12b0

Observation 2fff2e03-5f19-446d-8d9d-055967915801 · inbound

Practical, Generalizable and Robust Backdoor Attacks on Text-to-Image Diffusion Models cites this paper.

Practical, Generalizable and Robust Backdoor Attacks on Text-to-Image Diffusion Models Demystifying Prompts in Language Models via Perplexity Estimation

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T05:32:12.205549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:32:12.205549Z digest=sha256:d4f79e095ec213e0bfd6eab0ee7bcce5cfeb273e37e6bcaa7df44e95f2e0c11f

Observation e6e4c22f-6fcb-4a2d-b31b-6abcaf20cb44 · inbound

DisarmRAG: Stealthy Retriever-Centric Poisoning to Disable Self-Correction in Retrieval-Augmented Generation (Extended Version) cites this paper.

DisarmRAG: Stealthy Retriever-Centric Poisoning to Disable Self-Correction in Retrieval-Augmented Generation (Extended Version) Demystifying Prompts in Language Models via Perplexity Estimation

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T15:18:31.533223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:18:31.533223Z digest=sha256:345f7d029ad08a28cbe857a63b5cc53cba7c7af45f41d7ad6adb706cb75ffd1c

Observation 98b8de10-f98f-4fd3-a1e8-976a8184df6a · inbound

When Compression Becomes an Attack Surface: Black-Box Attacks on Prompt-Compressed LLM Agents cites this paper.

When Compression Becomes an Attack Surface: Black-Box Attacks on Prompt-Compressed LLM Agents Demystifying Prompts in Language Models via Perplexity Estimation

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-04T08:06:10.414127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:06:10.414127Z digest=sha256:a5da3e4aeb9842e555db6185c4082108cb2d8dc08062181bcddac89ea3c14ab4

Observation aed7c814-562a-4573-9efc-8265289b64b0 · inbound

SnapAudit: Active Auditing of Differentially Private In-Context Learning via Snapshot-Based Simulation cites this paper.

SnapAudit: Active Auditing of Differentially Private In-Context Learning via Snapshot-Based Simulation Demystifying Prompts in Language Models via Perplexity Estimation

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:22:09.003824Z

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.

source=pdf_text observed=2026-05-17T22:20:53.561649Z digest=sha256:25a0290e2c85d1aba75fa5bdefc693342c97b2627a59be565edc04bbe866f2e9

Observation 6e930568-0cf5-4606-a277-78d728a2bc79 · inbound

From Competition to Collaboration: Designing Sustainable Mechanisms Between LLMs and Online Forums cites this paper.

From Competition to Collaboration: Designing Sustainable Mechanisms Between LLMs and Online Forums Demystifying Prompts in Language Models via Perplexity Estimation

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T07:47:33.212432Z

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.

source=pdf_text observed=2026-05-16T07:42:48.141279Z digest=sha256:86fdaa3be906c4d9f562d2c0899076c442d664f084a761a8b4de5483426b5eb3

Observation 6de3def1-7496-478b-ace9-595ccd6f2632 · inbound

Linking Extreme Discourse to Structural Polarization in Signed Interaction Networks cites this paper.

Linking Extreme Discourse to Structural Polarization in Signed Interaction Networks Demystifying Prompts in Language Models via Perplexity Estimation

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T19:17:49.942420Z

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.

source=arxiv_source observed=2026-05-14T19:17:04.738168Z digest=sha256:eb70387c52adcdecd24e7c236881ab62dd4d942a89512ee9260ef9d07622241f

Observation 8e693294-61f2-4adb-a974-ec05af4acfc9 · inbound

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning cites this paper.

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning Demystifying Prompts in Language Models via Perplexity Estimation

Reference 187

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T09:59:45.004274Z

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.

source=arxiv_source observed=2026-06-26T09:19:50.623741Z digest=sha256:d10a7f3553ee7a32c8bb7720d5bb38bc7c7b13e76b6fb9799711902555a03f3d

Observation 210b8a92-797e-4b9d-ad08-875d4c03c995 · inbound

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning cites this paper.

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning Demystifying Prompts in Language Models via Perplexity Estimation

Reference 186

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T18:55:59.646841Z

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.

source=arxiv_source observed=2026-06-29T01:18:19.195007Z digest=sha256:db983f2c742e8cf4ce5dfac20799dda3209b20e07e483805c15aebec2ba9c5e7