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Paper Citation Record · LEDGER

Dynamic Data Mixing Maximizes Instruction Tuning for Mixture-of-Experts

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.11256.

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

pith.paper-citation-record.v1
2406.11256 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 2026-08-19T06:32:44.657259+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:36:50.443245Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T18:56:38.123142Z

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 1b12c9bf-e4cb-4149-982f-123b87521c93 · inbound

LLaMA-MoE v2: Exploring Sparsity of LLaMA from Perspective of Mixture-of-Experts with Post-Training cites this paper.

LLaMA-MoE v2: Exploring Sparsity of LLaMA from Perspective of Mixture-of-Experts with Post-Training Dynamic Data Mixing Maximizes Instruction Tuning for Mixture-of-Experts

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:38.994424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:02:38.994424Z digest=sha256:5396d154080e1d66fdc7eaad8b2bd80d91f2bc23a009097b5bf80500b552d155

Observation e84babf9-0795-400c-9617-7ad3585df5a9 · inbound

Mixture of Experts (MoE): A Big Data Perspective cites this paper.

Mixture of Experts (MoE): A Big Data Perspective Dynamic Data Mixing Maximizes Instruction Tuning for Mixture-of-Experts

Reference 226

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:56:38.130651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T18:56:38.051466Z digest=sha256:a3a2c44fb01f6aff472864db6cf4eb1a52b80aae1942f8c1eef258bf687cd72f

Observation af2a2846-6f1b-4689-ad35-bca8e2e2d71b · inbound

Mixture-of-Clustered-Experts: Advancing Expert Specialization and Generalization in Instruction Tuning cites this paper.

Mixture-of-Clustered-Experts: Advancing Expert Specialization and Generalization in Instruction Tuning Dynamic Data Mixing Maximizes Instruction Tuning for Mixture-of-Experts

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-15T16:36:50.443245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:36:50.443245Z digest=sha256:528ef42d15d1b0561b2ffeb29307b7d42ab7dd3ae674e7bd50f7fe80be116312