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Paper Citation Record · LEDGER

Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2305.03047.

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

pith.paper-citation-record.v1
2305.03047 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-19T20:28:38.900026Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T20:28:39.343804Z

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 697eb039-6409-4c1f-9779-dfc3180ed4c7 · inbound

Self-Refine: Iterative Refinement with Self-Feedback cites this paper.

Self-Refine: Iterative Refinement with Self-Feedback Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-10T20:47:39.794185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-10T20:47:39.476572Z digest=sha256:8dbc4c2cf4da5ed99fd3315b3f2398f2c270bda52402e108564d400d553efc45

Observation 2da9fe4a-93f7-4670-9612-6f7243aa63e8 · inbound

WizardLM: Empowering large pre-trained language models to follow complex instructions cites this paper.

WizardLM: Empowering large pre-trained language models to follow complex instructions Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 36

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T07:28:24.934997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-13T07:28:24.827546Z digest=sha256:889f10baa8ee03f9de3088b7878b2bbff0ec3235018bce1d1a9a90358f99c590

Observation 1c588287-7ba3-4e03-ab57-4cbfb878ed15 · inbound

Enhancing Chat Language Models by Scaling High-quality Instructional Conversations cites this paper.

Enhancing Chat Language Models by Scaling High-quality Instructional Conversations Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 256

Resolution
verified exact
arxiv_id, observed 2026-05-15T17:25:08.116138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-15T17:25:07.730933Z digest=sha256:de1eb0fc2d6f8883c0992e08933126d7d22dd0661302d1cade77d80641b4142d

Observation 6a1334bf-470b-4abc-8039-803db9ab18bd · inbound

Large Language Models are not Fair Evaluators cites this paper.

Large Language Models are not Fair Evaluators Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T12:10:42.450403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-17T12:10:42.248005Z digest=sha256:c6180cada7c5f2c3ef4bdfc916975b11145e0e23bae418fcba7d4a961ceb1a0e

Observation 37449b19-5bf3-498a-936b-eb9c7b7eb71e · inbound

Jailbroken: How Does LLM Safety Training Fail? cites this paper.

Jailbroken: How Does LLM Safety Training Fail? Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-14T18:17:42.960163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-14T18:17:42.752997Z digest=sha256:77221be5ea54b1fece644e4af5d65660bcef91e4829a5c4b546551e970f07c36

Observation e6a6b58d-e777-4124-8dec-ad135f754bac · inbound

A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 98

Resolution
verified exact
arxiv_id, observed 2026-05-19T20:28:39.345466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-19T20:28:38.900026Z digest=sha256:6c933d5c7d2ac54c04c08039d52a81e01775892cb76cb07afe6ef6887591c417

Observation 98fb852f-b97f-47e6-9a5f-3787f39e3f69 · inbound

Aligning Large Multimodal Models with Factually Augmented RLHF cites this paper.

Aligning Large Multimodal Models with Factually Augmented RLHF Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-15T17:58:17.929800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T17:58:17.699042Z digest=sha256:7c1522cbaf93ce5e330f958c9cd27bf0d16b5ab8c9f879398ab4f65c954ea7bf

Observation acfc37cf-3f99-4513-8f9b-83439727bb6b · inbound

Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! cites this paper.

Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T08:58:35.763820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T08:58:35.714394Z digest=sha256:d99eaee0bd002a60c604e4d4bc1f37ef3cf10e7c85af0130502d6f37c993e16a

Observation c9b0aad9-9dd6-45c0-ade3-e73ac5a1394c · inbound

TrustLLM: Trustworthiness in Large Language Models cites this paper.

TrustLLM: Trustworthiness in Large Language Models Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:17:08.340723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T11:17:08.108565Z digest=sha256:fd9f6618977d1d951701993f5793e38aec476b5cc96de304c45cd73a0928f8c4

Observation 2f35774d-e124-4c04-aaae-60f6d114ef7e · inbound

Large Language Models: A Survey cites this paper.

Large Language Models: A Survey Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 105

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:22:55.465842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T15:22:54.023279Z digest=sha256:55e6df00002e3c24b38776d0e6055c494b5b0f64d5e92e13e60675b8533b34d3

Observation 1d529ca8-ed5a-49c7-a837-ea0459261015 · inbound

Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models cites this paper.

Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T06:38:36.684446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-18T06:38:36.517935Z digest=sha256:f39e4c13301c0b1699c193da7e2fa14a15923a633b47dad8ac936472e6c8c3a1

Observation 036cc452-28e6-44e6-b711-31884c4e142b · inbound

STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator cites this paper.

STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:01:10.982816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T03:39:30.528601Z digest=sha256:06a80ecb74d4652b56ebdc0d85da993b9de49ee9dcc477757f93b8f92f9432f3