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Paper Citation Record · LEDGER

Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2209.11515.

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

pith.paper-citation-record.v1
2209.11515 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:34:33.109613Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T18:42:29.448304Z

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 46e02e05-a0ff-4923-a389-c00e2bb355e5 · inbound

kAgent: An execution-guided crash resolution agent for the Linux kernel cites this paper.

kAgent: An execution-guided crash resolution agent for the Linux kernel Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-16T05:34:33.109613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:34:33.109613Z digest=sha256:d8ec26b8be695bcddd6615ece7b2ff502755524a0dc80dc05af927d6414cb550

Observation edd9002e-6974-4ae2-a0f4-0a2cc9db4dba · inbound

SemAgent: A Semantics Aware Program Repair Agent cites this paper.

SemAgent: A Semantics Aware Program Repair Agent Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T19:26:51.151126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:26:51.151126Z digest=sha256:4a58b682e561f86402f13217fdaef85ed50572314571e6fa4e7b10fec42a9f99

Observation 78cb1406-69c6-4435-8ed4-295b2917eff7 · inbound

Sakura: An Approach for Generating Complex Tests from Natural Language Test Descriptions cites this paper.

Sakura: An Approach for Generating Complex Tests from Natural Language Test Descriptions Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-06-28T18:42:29.449676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-28T18:40:49.564295Z digest=sha256:3ddc2f66a1116efa4e1c5ece9676be1738c40bf8cc442425d896b45837fa1f04

Observation 679ee128-d73d-4cdb-9140-87e1af6b5c8d · inbound

Sakura: An Approach for Generating Complex Tests from Natural Language Test Descriptions cites this paper.

Sakura: An Approach for Generating Complex Tests from Natural Language Test Descriptions Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-04T04:56:44.157597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:56:44.157597Z digest=sha256:47a88b752a90e2d55bc81cc2fd159cce54c3aec95d2dc2ccf513a78e74a64db2

Observation 84b7aa66-2939-4043-b7a0-e3abdf81b81b · inbound

Coupling Planning with Episodic Memory in LLM Agents for Software Issue Resolution cites this paper.

Coupling Planning with Episodic Memory in LLM Agents for Software Issue Resolution Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T14:34:39.319335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:34:39.319335Z digest=sha256:dc112624544e338668a9b37b71d9179fde75cfd360a1e23dfe84bd9c1bd6ba2a