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Paper Citation Record · LEDGER

Generated Knowledge Prompting for Commonsense Reasoning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2110.08387.

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

pith.paper-citation-record.v1
2110.08387 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T22:41:21.159204Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T12:05:43.612430Z

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 7eabe71d-d10f-4271-af5c-89dc4ec44879 · inbound

FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance cites this paper.

FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance Generated Knowledge Prompting for Commonsense Reasoning

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T19:56:45.517500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T19:56:45.348973Z digest=sha256:7061c233d8c5a4d7217bb27f52b0e2df2c6c064925dec0d2be51958e17a8a1d7

Observation f3ecbb57-cc8f-4261-8769-c01d5debeac8 · inbound

INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation cites this paper.

INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation Generated Knowledge Prompting for Commonsense Reasoning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-09T22:41:21.159204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T22:41:21.159204Z digest=sha256:9878364f233f17b75987f42572c7f1021ed84e3e9b4895bf81d3dcb02f6ebbc9

Observation e29d5e5b-71d6-414e-9023-a1cc80353618 · inbound

Are MLMs Trapped in the Visual Room? cites this paper.

Are MLMs Trapped in the Visual Room? Generated Knowledge Prompting for Commonsense Reasoning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T12:54:25.942571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:54:25.942571Z digest=sha256:23277629a5eb916992c56ceb281b17e69a50862dbcb9fa950eb0f38b2a5792b2

Observation 53d3b50e-dbc1-4a73-80ea-ad435a7ecdbf · inbound

Commander-GPT: Dividing and Routing for Multimodal Sarcasm Detection cites this paper.

Commander-GPT: Dividing and Routing for Multimodal Sarcasm Detection Generated Knowledge Prompting for Commonsense Reasoning

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-19T08:22:10.899847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T08:20:56.561166Z digest=sha256:80b2db29e21e869a4c3938320a988ade414b71c2c1f24ef39d2237e9bcefba37

Observation fd73413d-c3a3-48cf-b9f0-4314da5146bc · inbound

Multimodal Large Language Models for End-to-End Affective Computing: Benchmarking and Boosting with Generative Knowledge Prompting cites this paper.

Multimodal Large Language Models for End-to-End Affective Computing: Benchmarking and Boosting with Generative Knowledge Prompting Generated Knowledge Prompting for Commonsense Reasoning

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T05:02:24.447997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:02:24.447997Z digest=sha256:a71c82a8c399c3647729311076f266a71974557602cb3913afe2c146ffd9caef

Observation 297f892f-6bb3-4268-8e92-2e0a94a8d17b · inbound

PARM: Pipeline-Adapted Reward Model cites this paper.

PARM: Pipeline-Adapted Reward Model Generated Knowledge Prompting for Commonsense Reasoning

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T09:28:39.520010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T05:15:26.015817Z digest=sha256:392ec5c0e88470dc633828ef7659f33eb0e3cdf7c9e1c531d691912bb4b33562

Observation 7f62326a-b95d-4059-ba0a-9479aaa7920f · inbound

A Single Rewrite Suffices: Empirical Lessons from Production Skill Description Optimization cites this paper.

A Single Rewrite Suffices: Empirical Lessons from Production Skill Description Optimization Generated Knowledge Prompting for Commonsense Reasoning

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-07-01T12:05:43.613801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-01T02:32:19.425550Z digest=sha256:9421f2b3756d535fba4d96fb304d6a9957bf452e4054b310530497ae69cfa339