Pith. sign in

Paper Citation Record · LEDGER

Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2410.13343.

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

pith.paper-citation-record.v1
2410.13343 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:06:23.099446Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T16:25:50.096535Z

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 d504e783-91b9-466c-a374-4615eae29432 · inbound

Navigating Shortcuts, Spurious Correlations, and Confounders: From Origins via Detection to Mitigation cites this paper.

Navigating Shortcuts, Spurious Correlations, and Confounders: From Origins via Detection to Mitigation Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models

Reference 212

Resolution
unresolved
no resolver link, observed 2026-08-11T20:53:27.037341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:53:27.037341Z digest=sha256:4b6e6ee2d074cc800bd834b87826c4f02aa6fa9093b9de07f0be4de1f0cc47b9

Observation 41938c65-3042-4641-aa69-bd352b9a093f · inbound

If Concept Bottlenecks are the Question, are Foundation Models the Answer? cites this paper.

If Concept Bottlenecks are the Question, are Foundation Models the Answer? Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-05-22T17:51:55.044662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-22T17:50:46.539215Z digest=sha256:f6db5cfbaf1b02dd6e0eceadbc56994f06a40e85682b44005f63ce05b7e21cd9

Observation efbe8f45-eff9-429e-aa30-2e4097fe2e87 · inbound

Physics-informed Temporal Alignment for Auto-regressive PDE Foundation Models cites this paper.

Physics-informed Temporal Alignment for Auto-regressive PDE Foundation Models Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-15T21:06:23.099446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:06:23.099446Z digest=sha256:5882720cb065a0123391c437601847b621a9364e3f557152797fb964591a712b

Observation 4396d72d-c56a-46f4-8dce-18bb2d67105d · inbound

Shortcut Learning in Generalist Robot Policies: The Role of Dataset Diversity and Fragmentation cites this paper.

Shortcut Learning in Generalist Robot Policies: The Role of Dataset Diversity and Fragmentation Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-05T22:50:43.783324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:50:43.783324Z digest=sha256:cb90c40e3ad9e104537a9c6b62d801ad73335d66cb086448ffff0ecf15509ead

Observation ef2660fb-d616-4381-8449-cb294b6ec5d7 · inbound

SPARSE Data, Rich Results: Few-Shot Semi-Supervised Learning via Class-Conditioned Image Translation cites this paper.

SPARSE Data, Rich Results: Few-Shot Semi-Supervised Learning via Class-Conditioned Image Translation Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-05T22:46:44.532064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:46:44.532064Z digest=sha256:80aac615b836e9297b8e3ea5ff2e8a3cdbf7be191d5cb8bbd113ee9c1c36a536

Observation 07dabac8-fc08-4959-b639-a16793d99bcc · inbound

Deciphering Shortcut Learning from an Evolutionary Game Theory Perspective cites this paper.

Deciphering Shortcut Learning from an Evolutionary Game Theory Perspective Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T05:50:26.712568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-08T19:29:59.568826Z digest=sha256:dc61e30ebdeaeb9aa660356dfe9a344b77d3e7d37e813799f5749e019d626239

Observation 199974fd-9cc0-4193-9c17-6630f20faaf8 · inbound

NeuroFlake: A Neuro-Symbolic LLM Framework for Flaky Test Classification cites this paper.

NeuroFlake: A Neuro-Symbolic LLM Framework for Flaky Test Classification Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-13T02:12:07.183973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-13T02:10:26.021153Z digest=sha256:16a41fb745ca1d60ee9fa80c762ba7170b9e38b2c3c6aaeceb9cbf009b4e8dca

Observation a95b62c1-6350-4e11-8548-729034136a62 · inbound

What LLMs explain is not what they believe: Evaluating explanation sufficiency under models' own input beliefs cites this paper.

What LLMs explain is not what they believe: Evaluating explanation sufficiency under models' own input beliefs Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models

Reference 134

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T16:25:50.097957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-06-30T00:38:21.949283Z digest=sha256:107833bef29c5a13ded3f6efef1bf80fd7b8a68f7ecbd027e6be9b7a11b35a2f