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Paper Citation Record · LEDGER

MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2205.00119.

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

pith.paper-citation-record.v1
2205.00119 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:10:00.335691Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T21:03:58.748181Z

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 4cc059b8-8ee4-44a6-8ce8-f7be90e52046 · inbound

BloombergGPT: A Large Language Model for Finance cites this paper.

BloombergGPT: A Large Language Model for Finance MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

Reference 141

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T23:19:46.598666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-13T23:19:46.231145Z digest=sha256:fd22dd5d6c88ae43e99acd8e7dec432725c1623432898c10b4ea4c4bad18cfeb

Observation ace95df2-273a-4228-8001-907658cae18c · inbound

PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel cites this paper.

PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-12T04:15:20.102935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-12T04:15:20.027659Z digest=sha256:a2702745a5d45b71b5ee740ed150cefc232a7362570d376037edc89e889cf275

Observation ae1087a2-d68d-443f-ae1d-f5168a54f64e · inbound

The Falcon Series of Open Language Models cites this paper.

The Falcon Series of Open Language Models MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

Reference 114

Resolution
verified exact
arxiv_id, observed 2026-05-16T09:46:09.892891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-16T09:46:09.701440Z digest=sha256:5f29690327d27d062f74befd946c7258d154084697dc38a61d27853ac41a125b

Observation 51bd6a73-b9cd-4b03-8802-1d55e0763222 · inbound

Pro-Prophet: A Systematic Load Balancing Method for Efficient Parallel Training of Large-scale MoE Models cites this paper.

Pro-Prophet: A Systematic Load Balancing Method for Efficient Parallel Training of Large-scale MoE Models MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-12T20:10:00.335691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:10:00.335691Z digest=sha256:f6feea695578b2da84f0f2ed01d8ccde3168a3084e7c784dae47c24c23f8ea58

Observation 1020e5c8-4152-42b0-86c7-a9f184107477 · inbound

Hiding Communication Cost in Distributed LLM Training via Micro-batch Co-execution cites this paper.

Hiding Communication Cost in Distributed LLM Training via Micro-batch Co-execution MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-12T13:53:07.484394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:53:07.484394Z digest=sha256:90bf5b32222898762d90912a0caaaf6fce66421d94ce8b15c7999e587ac60b54

Observation eb6af78d-5f49-40b9-a22b-54d9e8126298 · inbound

DiLoCoX: A Low-Communication Large-Scale Training Framework for Decentralized Cluster cites this paper.

DiLoCoX: A Low-Communication Large-Scale Training Framework for Decentralized Cluster MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T22:40:13.736781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:40:13.736781Z digest=sha256:9cf9315dec480e8ab490aebe6bab0098feb31f9b349897d54df26b885c9dc01c

Observation 21400e00-7801-467b-b69a-c3240e8fa5b8 · inbound

CommFuse: Hiding Tail Latency via Communication Decomposition and Fusion for Distributed LLM Training cites this paper.

CommFuse: Hiding Tail Latency via Communication Decomposition and Fusion for Distributed LLM Training MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:46:41.189739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-08T04:25:11.075964Z digest=sha256:38b6d6b780ed7d932b4f2202436506237251bf24e540949c90b1c7694d7eeba6

Observation 8ec76a35-bdb2-4da5-908e-b281d8097fd2 · inbound

Bandwidth-Aware and Cost-Efficient Pipeline Parallel Scheduling in Geo-Distributed LLM Training cites this paper.

Bandwidth-Aware and Cost-Efficient Pipeline Parallel Scheduling in Geo-Distributed LLM Training MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T21:03:58.749953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-29T20:55:37.983049Z digest=sha256:04db77c1b1ca82d74fb251b0be270b897878525f346a897b48e89ae953b7485f