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Paper Citation Record · LEDGER

SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents

As of 5 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 0 inbound Pith citation observations for arXiv:2602.11210.

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

pith.paper-citation-record.v1
2602.11210 v5

Coverage vector

measured 4 of 4 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T01:12:26.023882Z

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

4 of 4 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved3
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 19e6dc80-47e3-40c2-93f9-06fd7ff60be1 · outbound

This paper cites Evaluating Language Models for Efficient Code Generation.

SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents Evaluating Language Models for Efficient Code Generation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T01:12:25.863510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:12:25.863510Z digest=sha256:d6bafde961153f64bcea3e22b6100ab08f48fecf9e3fd99b16bc3b5724f920d2

Observation fd43b89c-91ad-4d56-adee-aee67ecd45af · outbound

This paper cites an unresolved cited work.

SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents Unresolved cited work

Reference 4

Resolution
malformed identifier
no resolver link, observed 2026-08-03T01:12:26.023882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:12:26.023882Z digest=sha256:3372cfc49052edc727786aca3e4f3a890a5ec6260ec32b1221d552b68e13ce51

Observation 1293886b-6af2-4af8-a279-25818ebf651d · outbound

This paper cites Evaluating Large Language Models Trained on Code.

SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents Evaluating Large Language Models Trained on Code

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-03T01:12:25.573850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:12:25.573850Z digest=sha256:ea81be4da3a8471f72c9d5644b97cb98d4405a221db84b8d554e30d3a7a9a89a

Observation 6a63d063-f8e5-4ef6-be1f-b85e31f5f5f3 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-03T01:12:25.702227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:12:25.702227Z digest=sha256:a112647f797ce48cdce359e3d49f9787fb9654ec3d7eeb98f8073e0621969680

Pith citing papers

No inbound Pith citation observations are available.