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Paper Citation Record · LEDGER

Dynamic Gradient Alignment for Online Data Mixing

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.02498.

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

pith.paper-citation-record.v1
2410.02498 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:27:57.434779Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T12:35:45.299249Z

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 161d34cb-2394-49f7-9871-818fd68db1ec · inbound

Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging cites this paper.

Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging Dynamic Gradient Alignment for Online Data Mixing

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-09T14:27:57.434779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:27:57.434779Z digest=sha256:3e41963580e103810ef71bb969c3a8cfb780117ab6244fb3710e41dd9bf0d8e0

Observation 9e77b75e-a9a1-4abf-8af6-eed623f1219b · inbound

GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining cites this paper.

GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining Dynamic Gradient Alignment for Online Data Mixing

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:04:22.974581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:04:22.974581Z digest=sha256:fad8464f547bca680c63bb16f44dcc1a5840b08cc395f50211bef3f99a14f210

Observation 51e9940f-84a8-4e96-885d-66991935c67f · inbound

Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning cites this paper.

Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning Dynamic Gradient Alignment for Online Data Mixing

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:35:45.364390Z

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=2026-08-07T12:35:40.028666Z digest=sha256:a1c0d5818f2c1e6a05ff1df6cca87d8ae761dec5cb8051e173022d138048747a