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Paper Citation Record · LEDGER

Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models

As of 31 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2508.01908.

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

pith.paper-citation-record.v1
2508.01908 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-31T06:34:12.847434+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T19:12:02.449224Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:48:39.916449Z

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 28eae9c9-ad32-4ff1-9ee2-4bcb1070b2b1 · inbound

Replay-Based Continual Learning for Physics-Informed Neural Operators cites this paper.

Replay-Based Continual Learning for Physics-Informed Neural Operators Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:36:07.379818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-08T17:22:32.572495Z digest=sha256:4e15dbe3de12b2e0906f360513324fb2b712f1391b42d5b11c44a6bf8e2efbd9

Observation 26b92e98-9bb6-4a39-97fa-d2b3a55114bb · inbound

Attribution-Guided Continual Learning for Large Language Models cites this paper.

Attribution-Guided Continual Learning for Large Language Models Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T18:11:05.469303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-08T16:31:15.098964Z digest=sha256:6a65e13df937bf067c09994180aa52d94ab5e8714b60b2c5da9413c5ed29fd6b

Observation a67f3097-a470-451e-a6da-38bf27867707 · inbound

Attribution-Guided Continual Learning for Large Language Models cites this paper.

Attribution-Guided Continual Learning for Large Language Models Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-14T19:12:02.449224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T19:12:02.449224Z digest=sha256:3e659a0e4995ca0af6660e36ed53a84a58a7cca0f778aedc1c15448ff0339354

Observation 375b4ee8-4a09-48aa-9365-84847ad83b16 · 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 Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-19T17:07:41.616092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-05-19T17:06:12.280460Z digest=sha256:5752d02c2afb07870402868b3b3c528274a502f776eae2b32b55350200bd22a2

Observation a41a8f0d-3fa0-42f9-9ccc-ae9208b21486 · inbound

Dynamic Proxy-Mixing: Transferring Replay Controllers from Small to Large Models for Continual Instruction Tuning cites this paper.

Dynamic Proxy-Mixing: Transferring Replay Controllers from Small to Large Models for Continual Instruction Tuning Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-06-28T23:02:46.614917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=arxiv_source observed=2026-06-28T22:58:30.457420Z digest=sha256:c84924c0895aa502d6febf3b28632be7c0164556d7929af3cdb7cf06cfda5717

Observation 63d1d254-97b2-484a-acc7-bcfaadbeaedd · inbound

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning cites this paper.

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:48:39.917678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

source=pdf_text observed=2026-06-27T05:02:18.347642Z digest=sha256:2e2303138e936ea0e9163def409d1f31d4fecade31e738e09041c5022f78c196