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Paper Citation Record · LEDGER

Taming Sparsely Activated Transformer with Stochastic Experts

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2110.04260.

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

pith.paper-citation-record.v1
2110.04260 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-02T15:14:36.946247Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T15:17:07.182288Z

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 202a855d-5903-44e1-bd12-8d1df84630b8 · inbound

DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models cites this paper.

DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models Taming Sparsely Activated Transformer with Stochastic Experts

Reference 167

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:07:22.292061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-13T01:07:22.166595Z digest=sha256:d490604a1bfd5624d4f00d46357db9c1ddd22673cd879984e117fe4d2ef94cf7

Observation 543a92b1-cf1d-4faf-8ffe-6e152c431736 · inbound

MEPA: Multi-Scale Representation Alignment for Visual Autoregressive Modeling with Mixture of Experts cites this paper.

MEPA: Multi-Scale Representation Alignment for Visual Autoregressive Modeling with Mixture of Experts Taming Sparsely Activated Transformer with Stochastic Experts

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-07-02T15:17:07.183793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-02T15:14:36.946247Z digest=sha256:897f9567515d80b3edcfefd94e13c8d076324d285e71a0c9792c77f3e76bc69c