Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:22:17.450459Z
Paper Citation Record · LEDGER
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection
As of 14 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:2507.10583.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T12:30:50.134299Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T12:30:50.301731Z
Reference resolution
12 of 12 outbound references displayed
- verified exact0
- verified fuzzy5
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 40d95899-2211-40e8-9caa-c25349b49288 · outbound
This paper cites Yi: Open Foundation Models by 01.AI.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection Yi: Open Foundation Models by 01.AI
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:22:17.386412Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c84d6a18-dfbf-4a53-ab8d-26ea4a88dc56 · outbound
This paper cites b a s i c a l l y say i ti s 1−D.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection b a s i c a l l y say i ti s 1−D
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:22:17.586667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation e98ced8b-5b5b-4e0d-9981-e0a6db140033 · outbound
This paper cites In Proceedings of the 21st In- ternational Conference on Mining Software Reposito- ries, MSR ’24, page 394–406, New York, NY , USA.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection In Proceedings of the 21st In- ternational Conference on Mining Software Reposito- ries, MSR ’24, page 394–406, New York, NY , USA
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:22:17.668875Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation fcc12f47-8625-41b7-bed7-8728820880de · outbound
This paper cites The Heap: A Contamination-Free Multilingual Code Dataset for Evaluating Large Language Models.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection The Heap: A Contamination-Free Multilingual Code Dataset for Evaluating Large Language Models
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:22:17.415772Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36950266-4941-48c5-8725-d2ffa9579451 · outbound
This paper cites an unresolved cited work.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T18:22:17.618894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation e91a3fb1-e85f-40c2-b894-015a01dc9466 · outbound
This paper cites CoDet-M4: Detecting Machine-Generated Code in Multi-Lingual, Multi-Generator and Multi-Domain Settings.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection CoDet-M4: Detecting Machine-Generated Code in Multi-Lingual, Multi-Generator and Multi-Domain Settings
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:22:17.434950Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c8cf9ae6-8c4d-49c9-a9ee-44b95985cc4f · outbound
This paper cites Enclose this summary within [ SUMMARY ] and [/ SUMMARY ] tags.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection Enclose this summary within [ SUMMARY ] and [/ SUMMARY ] tags
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:22:17.604209Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 4334ab84-5d2f-4f14-9a61-1c421b641368 · outbound
This paper cites TACO: Topics in Algorithmic COde generation dataset.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection TACO: Topics in Algorithmic COde generation dataset
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:22:17.426395Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 63cea494-16ed-44fe-9104-7866d86e7ff1 · outbound
This paper cites Can AI-Generated Text be Reliably Detected?.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection Can AI-Generated Text be Reliably Detected?
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:22:17.440421Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aba84ffb-0ac4-4c3d-901b-8c660f8e8b74 · outbound
This paper cites Efficient Training of Language Models to Fill in the Middle.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection Efficient Training of Language Models to Fill in the Middle
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:22:17.392318Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation da2cd641-4ad5-4ec2-9e7c-9fcb1be473fe · outbound
This paper cites In The Thirteenth In- ternational Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection In The Thirteenth In- ternational Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025
Reference 2025
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:22:17.652820Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 93fc2803-64a4-470b-afb8-5fbf8e69566f · outbound
This paper cites Jessica Ji, Jenny Jun, Maggie Wu, and Rebecca Gelles.
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection Jessica Ji, Jenny Jun, Maggie Wu, and Rebecca Gelles
Reference 2309
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T18:22:17.638328Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Pith citing papers
Observation ee31a374-c6aa-472c-87a4-f12ee64d08ca · inbound
MultiAIGCD: A Comprehensive dataset for AI Generated Code Detection Covering Multiple Languages, Models,Prompts, and Scenarios cites this paper.
MultiAIGCD: A Comprehensive dataset for AI Generated Code Detection Covering Multiple Languages, Models,Prompts, and Scenarios $\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection
Reference 21
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T12:30:50.305460Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.