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Paper Citation Record · LEDGER

Law of the Weakest Link: Cross Capabilities of Large Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.19951.

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

pith.paper-citation-record.v1
2409.19951 v2

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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:59:01.351042Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T21:05:04.559699Z

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 71a16bef-a5f7-43dc-a220-6ece9adb0772 · inbound

BTS: Harmonizing Specialized Experts into a Generalist LLM cites this paper.

BTS: Harmonizing Specialized Experts into a Generalist LLM Law of the Weakest Link: Cross Capabilities of Large Language Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-09T21:59:01.351042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T21:59:01.351042Z digest=sha256:3d906dd0583d0bd29fbfaf31220bbe724c3f6f2611a2773d810f89beb29e8c7b

Observation 9f792b22-1b5f-4fe1-ba87-a930415692ca · inbound

RAGtifier: Evaluating RAG Generation Approaches of State-of-the-Art RAG Systems for the SIGIR LiveRAG Competition cites this paper.

RAGtifier: Evaluating RAG Generation Approaches of State-of-the-Art RAG Systems for the SIGIR LiveRAG Competition Law of the Weakest Link: Cross Capabilities of Large Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T00:23:11.654664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:23:11.654664Z digest=sha256:d94cb26773f20a6e6c0b443b29690822c96b945577d40fdd0bcaeec397165346

Observation 032691c2-97b1-4b14-ad36-fec91d514772 · inbound

DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts cites this paper.

DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts Law of the Weakest Link: Cross Capabilities of Large Language Models

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-19T15:52:38.666818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-19T15:48:59.800756Z digest=sha256:dbd52b54603516a73cc51ded9ab647ea0378e95719441ab99096556ba3bb5740

Observation 46ddb388-1c9e-4e39-82e4-51da90680c89 · inbound

DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts cites this paper.

DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts Law of the Weakest Link: Cross Capabilities of Large Language Models

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-06-30T21:05:04.561281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-30T20:58:51.141871Z digest=sha256:46d696371f30e47d93667cfcc459641149a87cfe59d6f2b524e4ccb67ad3f094

Observation 9b192107-bb25-4d91-bef1-e0f89282f072 · inbound

DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts cites this paper.

DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts Law of the Weakest Link: Cross Capabilities of Large Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-02T14:03:10.172249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T14:03:10.172249Z digest=sha256:763c0e4dc5ec4d6a7e2f0c921144f1fc8b6dd413721fec9a88703f0361bb2d45