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Paper Citation Record · LEDGER

Examining Forgetting in Continual Pre-training of Aligned Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2401.03129.

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

pith.paper-citation-record.v1
2401.03129 v1

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 2026-08-07T11:10:14.591621Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T13:48:20.831541Z

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 2a9180e8-9065-4d9c-88cf-e10125918815 · inbound

The Future of Continual Learning in the Era of Foundation Models: Three Key Directions cites this paper.

The Future of Continual Learning in the Era of Foundation Models: Three Key Directions Examining Forgetting in Continual Pre-training of Aligned Large Language Models

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-07T11:10:14.591621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:14.591621Z digest=sha256:b54a2ac56459a5d6b1639e29937ac650f4c98833a95f77836906e6697da09e67

Observation aa24de08-ac04-4c7c-afc1-dbd5d3a855b7 · inbound

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead Examining Forgetting in Continual Pre-training of Aligned Large Language Models

Reference 176

Resolution
unresolved
no resolver link, observed 2026-08-06T21:36:36.500838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:36:36.500838Z digest=sha256:5df403bd11d6c9fc12a787e550da2b896149309e9f8d79da2e07ea36a23fe5e7

Observation fa4d997f-22b2-4ef9-a464-7ee36f46cdab · inbound

TFGN: Task-Free, Replay-Free Continual Pre-Training Without Catastrophic Forgetting at LLM Scale cites this paper.

TFGN: Task-Free, Replay-Free Continual Pre-Training Without Catastrophic Forgetting at LLM Scale Examining Forgetting in Continual Pre-training of Aligned Large Language Models

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-19T17:07:41.600164Z

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=2026-05-19T17:06:12.280460Z digest=sha256:ecf318dd4b89508fb94f1a2e11ca55325c84ae8ad40c4b0d7198d66bcd5a4b41

Observation ed0aad0a-f824-40c9-918a-3c379bb87050 · inbound

Max-Window Scale Estimation for Near-Lossless HiF8 W8A8 Quantization-Aware Training cites this paper.

Max-Window Scale Estimation for Near-Lossless HiF8 W8A8 Quantization-Aware Training Examining Forgetting in Continual Pre-training of Aligned Large Language Models

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T23:04:00.899086Z

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=2026-06-29T23:02:56.306685Z digest=sha256:0321cb89d709d060a2ec6090c2d086bf902e402b6ee8d27e009f76bd4959e642

Observation 7f374d50-fc67-4f01-b9b7-4f0970afb7b8 · inbound

SupraBench: A Benchmark for Supramolecular Chemistry cites this paper.

SupraBench: A Benchmark for Supramolecular Chemistry Examining Forgetting in Continual Pre-training of Aligned Large Language Models

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T13:48:20.832777Z

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=2026-06-27T07:34:11.596337Z digest=sha256:5045d2a10cd98a947833a4e6218bae29bcd1ce10fb893589039c5152e9e98cbd