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Paper Citation Record · LEDGER

CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1911.03705.

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

pith.paper-citation-record.v1
1911.03705 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:51:56.178831Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:09:27.769806Z

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 c862f7a3-6295-4026-a797-842f31c623c9 · inbound

Generative Language Models Potential for Requirement Engineering Applications: Insights into Current Strengths and Limitations cites this paper.

Generative Language Models Potential for Requirement Engineering Applications: Insights into Current Strengths and Limitations CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning

Reference 129

Resolution
unresolved
no resolver link, observed 2026-08-12T04:51:56.178831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:51:56.178831Z digest=sha256:2530bad7707e1b29d6ac8bc5e1cefedf6396dd5fa83ef1fc5d0fcb416f05a80f

Observation 22fbca40-f542-4007-bfa0-8653d4cfba24 · inbound

Randomly Sampled Language Reasoning Problems Elucidate Limitations of In-Context Learning cites this paper.

Randomly Sampled Language Reasoning Problems Elucidate Limitations of In-Context Learning CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-10T22:10:33.915800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:10:33.915800Z digest=sha256:1f5f08602285c44a8d8362861c91314e86fae03f26ac1799148f32dfc9027a20

Observation 768072a0-849d-4009-a7cd-a362007efa69 · inbound

Generative Adversarial Networks Bridging Art and Machine Intelligence cites this paper.

Generative Adversarial Networks Bridging Art and Machine Intelligence CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning

Reference 184

Resolution
unresolved
no resolver link, observed 2026-08-08T23:30:59.369982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T23:30:59.369982Z digest=sha256:48dcc2b3c8ccfc26d06ca0aff61c2901b6342aeb4031b0a0486904e1476b263b

Observation 90e7a69b-c29d-4437-a1d3-25f249c3f4c6 · inbound

Learning to Select In-Context Demonstration Preferred by Large Language Model cites this paper.

Learning to Select In-Context Demonstration Preferred by Large Language Model CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:09:27.838104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-07T14:09:23.025954Z digest=sha256:36375d07b15ef6f8f6e414f917e99b74a48f955208f9204c92f96fbb462acff5