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Paper Citation Record · LEDGER

JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2411.00142.

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

pith.paper-citation-record.v1
2411.00142 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:07:19.396156Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T00:28:29.939882Z

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 c1f95b5f-4a7c-4ea5-a941-e8ef8f4e1ed9 · inbound

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods cites this paper.

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking

Reference 171

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:11:13.192804Z

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=pdf_text observed=2026-05-11T23:08:34.312466Z digest=sha256:817f7029aba6a6a77a8c5a579c52448c0287b87ee3791d3679b734ddd0ab9826

Observation ee029978-a80e-452e-8c8e-1524b60a1823 · inbound

TongSearch-QR: Reinforced Query Reasoning for Retrieval cites this paper.

TongSearch-QR: Reinforced Query Reasoning for Retrieval JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T04:07:19.396156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:07:19.396156Z digest=sha256:05f143ad3a3113966cac35ca4fdb12ce0009ea25695b3c20b4f44d216f3f7695

Observation 3f13f3b9-f177-4405-b6a1-24c6e3956c63 · inbound

Shifting from Ranking to Set Selection for Retrieval Augmented Generation cites this paper.

Shifting from Ranking to Set Selection for Retrieval Augmented Generation JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T18:57:33.601899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:57:33.601899Z digest=sha256:bf1976afd97ebe624ca538d8224f594a1bb6eb7a8f58944eb6d8e0aeaeb4fc5d

Observation 8e3fadea-c81b-42bc-a8f8-ba5419fd6e89 · inbound

ERank: Fusing Supervised Fine-Tuning and Reinforcement Learning for Effective and Efficient Text Reranking cites this paper.

ERank: Fusing Supervised Fine-Tuning and Reinforcement Learning for Effective and Efficient Text Reranking JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-05T13:36:38.010031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:36:38.010031Z digest=sha256:718fb755d3889eca95741261af279e9ace389fe2aaaa0b7c20b54ef65b2ba3af

Observation f65d598e-d030-4748-b892-a4f5bf7e5243 · inbound

Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference cites this paper.

Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-14T00:28:29.943936Z

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=pdf_text observed=2026-05-14T00:25:49.807277Z digest=sha256:cf0995ca51ba6bd79ddd49aba4305ac2907e6c9b0046e5b3775b0e82c414b088

Observation 897dd2d3-740f-4c91-bb97-6e50aad20b6c · inbound

NeocorRAG: Less Irrelevant Information, More Explicit Evidence, and More Effective Recall via Evidence Chains cites this paper.

NeocorRAG: Less Irrelevant Information, More Explicit Evidence, and More Effective Recall via Evidence Chains JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking

Reference 33

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T10:11:28.039728Z

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=pdf_text observed=2026-05-07T07:19:44.756174Z digest=sha256:33af7bdabd80bb8b082af42b5bd039c7383d1558ba15c247fa235cf14b728842

Observation 99c4fa14-bebd-4817-92f1-e5811ce68979 · inbound

A Survey of Reasoning-Intensive Retrieval: Progress and Challenges cites this paper.

A Survey of Reasoning-Intensive Retrieval: Progress and Challenges JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:56:05.102386Z

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=2026-05-09T20:53:05.314601Z digest=sha256:6103ab132d4acecb0ed37600273d2240ff6c9dfa5bfbae7ded7b77525d68f78e