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Paper Citation Record · LEDGER

Self-Boosting Large Language Models with Synthetic Preference Data

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2410.06961.

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

pith.paper-citation-record.v1
2410.06961 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:59:52.814369Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T15:35:47.622062Z

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 4a944236-372a-4938-993c-539c86c6c0a6 · 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 Self-Boosting Large Language Models with Synthetic Preference Data

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:08:36.358358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-11T23:08:34.312466Z digest=sha256:68470ad06a382d097274769f5d114562c8c5d13eec6c241ee534016795b2ec2d

Observation fba7583b-1717-4553-a9f9-b7f8b80d04d3 · inbound

Amulet: Putting Complex Multi-Turn Conversations on the Stand with LLM Juries cites this paper.

Amulet: Putting Complex Multi-Turn Conversations on the Stand with LLM Juries Self-Boosting Large Language Models with Synthetic Preference Data

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T13:59:52.814369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:59:52.814369Z digest=sha256:6891d7b728b7eee69fca58f56984026e649c633f3a8f16c0459469ff2c50deb9

Observation d38a2290-f18f-47e1-a916-e0d9b553976b · inbound

Data Swarms: Optimizable Generation of Synthetic Evaluation Data cites this paper.

Data Swarms: Optimizable Generation of Synthetic Evaluation Data Self-Boosting Large Language Models with Synthetic Preference Data

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:35.341828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:03:35.341828Z digest=sha256:a2d72a8bc9a0905feb0f7c85ce5d045da0ab5428e10310e327df2f5bf7f781c6

Observation 710738de-a91c-4664-8a43-71f3c1dc08e5 · inbound

RACE-Align: Retrieval-Augmented and Chain-of-Thought Enhanced Preference Alignment for Large Language Models cites this paper.

RACE-Align: Retrieval-Augmented and Chain-of-Thought Enhanced Preference Alignment for Large Language Models Self-Boosting Large Language Models with Synthetic Preference Data

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T11:21:41.210733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:21:41.210733Z digest=sha256:4fa6b66dea5ed8766d2eae39e50df3b4d444a062ae6791771527208e40fcd963

Observation 0033f159-6de3-49f9-9d73-1523e9f65203 · inbound

SGPO: Self-Generated Preference Optimization based on Self-Improver cites this paper.

SGPO: Self-Generated Preference Optimization based on Self-Improver Self-Boosting Large Language Models with Synthetic Preference Data

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T13:49:09.839915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:49:09.839915Z digest=sha256:84fac0b1eb5ca3596fd86ce136f09427bc2196f6650411a94abf1cefea24e943

Observation 36c23218-19d4-4bd1-948b-c87a393ded2e · inbound

Generating Leakage-Free Benchmarks for Robust RAG Evaluation cites this paper.

Generating Leakage-Free Benchmarks for Robust RAG Evaluation Self-Boosting Large Language Models with Synthetic Preference Data

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-12T03:06:18.914646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-12T03:04:39.253429Z digest=sha256:f5bd379f1597f5a4ea96c8d0f0acd2940c1385130ebbb29ddce3ac68eaedc2e8

Observation 7db188be-aa53-42ca-8282-19b1ea406ca6 · inbound

Towards Human-Level Book-Writing Capability cites this paper.

Towards Human-Level Book-Writing Capability Self-Boosting Large Language Models with Synthetic Preference Data

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-20T15:43:27.028612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T15:40:53.245419Z digest=sha256:abee595b84a27b6f481785b4d970693cee94d09b3a53a93952417825120e1bcb

Observation bd3eb026-eb57-469c-990f-014da09e127d · inbound

Towards Human-Level Book-Writing Capability cites this paper.

Towards Human-Level Book-Writing Capability Self-Boosting Large Language Models with Synthetic Preference Data

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-06-30T19:05:00.337562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T19:03:27.257098Z digest=sha256:004624ad75e8b3e7e0db902df9c4019839786399af92d5ecf176bec9201f5600

Observation 2d053009-9f22-441b-b15e-b5e541e3f504 · inbound

Vision-driven Preference Synthesis for Mitigating Hallucinations in VLMs cites this paper.

Vision-driven Preference Synthesis for Mitigating Hallucinations in VLMs Self-Boosting Large Language Models with Synthetic Preference Data

Reference 74

Resolution
verified exact
arxiv_id, observed 2026-07-01T15:35:47.623531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T01:22:16.176398Z digest=sha256:b5bb6157633753e6f0262b958a2d0c0d41b763e15baab00b04ebaab1d5aa4327