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Paper Citation Record · LEDGER

Improving Passage Retrieval with Zero-Shot Question Generation

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2204.07496.

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

pith.paper-citation-record.v1
2204.07496 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:07:49.413784Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T22:34:24.166506Z

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 b00b584f-1290-4481-b66f-0327247f961c · inbound

Rank It, Then Ask It: Input Reranking for Maximizing the Performance of LLMs on Symmetric Tasks cites this paper.

Rank It, Then Ask It: Input Reranking for Maximizing the Performance of LLMs on Symmetric Tasks Improving Passage Retrieval with Zero-Shot Question Generation

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-12T05:21:55.149300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:21:55.149300Z digest=sha256:7c72aa267686ec98c2536ec0bff0a0e7455ff76ffb8b213add8457bb511d4320

Observation ba4a8530-dc47-4a57-9e0b-369a93f59127 · inbound

DynRank: Improving Passage Retrieval with Dynamic Zero-Shot Prompting Based on Question Classification cites this paper.

DynRank: Improving Passage Retrieval with Dynamic Zero-Shot Prompting Based on Question Classification Improving Passage Retrieval with Zero-Shot Question Generation

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T05:16:44.361871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:16:44.361871Z digest=sha256:d7e3f088ca8076b4845414f11ac70315337509f3b6e1ba6fa6f39044f8834754

Observation c78153ab-6dbf-4104-8d02-3dbd13e86432 · inbound

Multilingual Open QA on the MIA Shared Task cites this paper.

Multilingual Open QA on the MIA Shared Task Improving Passage Retrieval with Zero-Shot Question Generation

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T21:43:28.576269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T21:43:28.576269Z digest=sha256:54bd61f5a4472719fd570b662f24adb69e827f85547522d5c2e0497edd103246

Observation 32f8d33e-f92f-4150-a159-c2a10ba338a2 · inbound

ASRank: Zero-Shot Re-Ranking with Answer Scent for Document Retrieval cites this paper.

ASRank: Zero-Shot Re-Ranking with Answer Scent for Document Retrieval Improving Passage Retrieval with Zero-Shot Question Generation

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T14:32:38.016980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:32:38.016980Z digest=sha256:b20e1d9dfea81331771c12ad10553c5211c9026c355a0e218cc446e059e0c724

Observation efc28b23-128b-4a5d-ab29-579b33c1cc00 · inbound

Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation cites this paper.

Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation Improving Passage Retrieval with Zero-Shot Question Generation

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-09T12:07:24.183318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:07:24.183318Z digest=sha256:0605bbd7ac535135d8b534f7bb8a38bf2a992b4b39f46abcfd20dffba1db1579

Observation 7151b34b-bf0b-4a88-8da6-df56d502a40f · inbound

Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models cites this paper.

Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models Improving Passage Retrieval with Zero-Shot Question Generation

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-16T00:07:49.413784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:07:49.413784Z digest=sha256:1d3b2df37f6f028844f86d0ff6c24a40f5e61b84ec23864651c622df5a979d54

Observation b5429959-4afd-4f15-8f3c-9ab1d81d6170 · inbound

DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation cites this paper.

DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation Improving Passage Retrieval with Zero-Shot Question Generation

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-15T22:27:09.638724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:27:09.638724Z digest=sha256:ec15245cffdd34a975baccfeffdc64363e59b9cc0c4f62b1fe2b405d782a9a5b

Observation 5dd0f00c-093f-427e-b82d-a41103713bd8 · inbound

QUPID: Quantified Understanding for Enhanced Performance, Insights, and Decisions in Korean Search Engines cites this paper.

QUPID: Quantified Understanding for Enhanced Performance, Insights, and Decisions in Korean Search Engines Improving Passage Retrieval with Zero-Shot Question Generation

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T22:22:45.782782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:22:45.782782Z digest=sha256:d5c579c77a5e38fb4c4ccc7bf862a8ecc2cd462671c704551aea7641d183623d

Observation df95bbe0-19a8-4339-a387-142647be3a9f · inbound

REARANK: Reasoning Re-ranking Agent via Reinforcement Learning cites this paper.

REARANK: Reasoning Re-ranking Agent via Reinforcement Learning Improving Passage Retrieval with Zero-Shot Question Generation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T14:07:13.912679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:07:13.912679Z digest=sha256:fcb8144fe397e3212a58b44f1d0b597a54a0813c6c9d2a5663f764a3cb707a80

Observation ac4c30c2-d26e-4adb-ac30-997cc537f5ec · inbound

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems cites this paper.

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems Improving Passage Retrieval with Zero-Shot Question Generation

Reference 150

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:52:16.354453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-19T11:49:36.574471Z digest=sha256:ec7ff903d1314101cbbd31bf4cf1a3c7b2d44360b8072e34f3dd5fc89fd030ca

Observation f71f28c1-f1a6-4e61-ab41-3cdce5021d4b · inbound

How Good are LLM-based Rerankers? An Empirical Analysis of State-of-the-Art Reranking Models cites this paper.

How Good are LLM-based Rerankers? An Empirical Analysis of State-of-the-Art Reranking Models Improving Passage Retrieval with Zero-Shot Question Generation

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-05T17:15:15.356287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:15:15.356287Z digest=sha256:7a1e83af1f3e6cc52722854308cf5c7b50f2d363a65c4b8a0b08e7119b838fe9

Observation eb041e6c-1338-45b7-b2e4-adab35deed04 · inbound

Access Paths for Efficient Ordering with Large Language Models cites this paper.

Access Paths for Efficient Ordering with Large Language Models Improving Passage Retrieval with Zero-Shot Question Generation

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-21T22:34:24.168951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-21T22:32:23.352584Z digest=sha256:d53e4c0f2626338d5d0ae767735350e279157bf9f8d4a0235eff1e44d735bfc9

Observation 51e6f7f8-93ac-48a4-b627-baad6d38a8fd · inbound

Rethinking the Necessity of Adaptive Retrieval-Augmented Generation through the Lens of Adaptive Listwise Ranking cites this paper.

Rethinking the Necessity of Adaptive Retrieval-Augmented Generation through the Lens of Adaptive Listwise Ranking Improving Passage Retrieval with Zero-Shot Question Generation

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-10T08:27:51.788277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T08:26:02.605596Z digest=sha256:5fac65d6cc2b93ae002b1fca5a08619388d4e9a5541d7fe49219dc4c6dd541c2