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Paper Citation Record · LEDGER

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models

As of 14 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 1 inbound Pith citation observation for arXiv:2507.15868.

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

pith.paper-citation-record.v1
2507.15868 v1

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:26:58.398605Z

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-14T17:43:48.456679Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T17:49:23.561376Z

Reference resolution

10 of 10 outbound references displayed

  • verified exact0
  • verified fuzzy5
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1a497670-7b41-4cbb-b7e6-25af520195d5 · outbound

This paper cites LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T17:26:57.798530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:26:57.798530Z digest=sha256:b943439a7ce27e9e705400600a61364b2c8eae53547b342db50176e91dc1fc09

Observation 545bc79d-90d7-4a0c-a540-2cf8b4bf5d9d · outbound

This paper cites Halstead.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models Halstead

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:26:59.132730Z

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.

source=pdf_text observed=2026-08-06T17:26:57.884653Z digest=sha256:a107b120579172d0421872d5e54ca1efb0af26965952df8fe580d08a50a5174d

Observation 99e5430a-a6ad-4153-b26f-3c63df448ba0 · outbound

This paper cites Adversarial ex- amples for evaluating reading comprehen- sion systems.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models Adversarial ex- amples for evaluating reading comprehen- sion systems

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:26:59.000290Z

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.

source=pdf_text observed=2026-08-06T17:26:57.959899Z digest=sha256:ca3ff9471ee759864ac29ce418205d178979de2073712894672cd8f0e9f33a8c

Observation e45d585c-6a1d-4fc7-ab1c-e4c385131356 · outbound

This paper cites On faith- fulness and factuality in abstractive sum- marization.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models On faith- fulness and factuality in abstractive sum- marization

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:26:58.905222Z

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.

source=pdf_text observed=2026-08-06T17:26:58.029361Z digest=sha256:805734275c07a4343978a12675faec81acb229961f0c34100a3fc33d0c6b2036

Observation 6aad6d91-519d-4a76-ad5f-2a5e53c6c458 · outbound

This paper cites Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T17:26:58.094112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:26:58.094112Z digest=sha256:27b3060cf66e69424383fe144b710419f3ab2553465ca3673c974fc12c159097

Observation 40cacaab-bdfc-4206-80c1-3fe77daf5e67 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T17:26:58.175019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:26:58.175019Z digest=sha256:468671b9dca1db3eb10bba1808433091af38aed58efe45b31218c3dad70c02f4

Observation 09b41dde-eeb1-464e-b564-beb7cf2a7739 · outbound

This paper cites Univer- sal adversarial triggers for attacking and an- alyzing NLP.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models Univer- sal adversarial triggers for attacking and an- alyzing NLP

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:26:58.771370Z

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.

source=pdf_text observed=2026-08-06T17:26:58.222319Z digest=sha256:91f603fba0defc46d9861d680eca4aa0c12e92f261b8015cff2e32ce5af6770f

Observation 99e8532f-c972-49c5-884b-903363f99cc0 · outbound

This paper cites Don’t take the easy way out: Ensemble based methods for avoid- ing known dataset biases.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models Don’t take the easy way out: Ensemble based methods for avoid- ing known dataset biases

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:26:58.623531Z

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.

source=pdf_text observed=2026-08-06T17:26:58.300798Z digest=sha256:af30f52eaba86c7a7ba89839cfe6df39bf0136765ee0e32e09c3e4d5d4900815

Observation 3c6a8bfe-7fae-4a1d-9d39-17efd68b6a66 · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T17:26:58.346488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:26:58.346488Z digest=sha256:43d90d3f407451f2f466c27f4c9912aa133dee16677974d9bf5639705c90ca37

Observation db0697e7-fef1-419d-8dab-d1b460a130e7 · outbound

This paper cites Holistic Evaluation of Language Models.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models Holistic Evaluation of Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T17:26:58.398605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:26:58.398605Z digest=sha256:5d262d8387733b1888112bc40db30bdebfb78dfa2424516750fa0e31d47df688

Pith citing papers

Observation 97a4f4e8-8bda-4573-83b9-0eee35b170c4 · inbound

Learning Perturbations to Extrapolate Your LLM cites this paper.

Learning Perturbations to Extrapolate Your LLM Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-14T17:49:23.563898Z

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.

source=arxiv_source observed=2026-05-14T17:43:48.456679Z digest=sha256:83335851fbc6aa3b5023b0bed2bcfc9eb461dafca52293a131d83b186e197ce3