Paper Citation Record · LEDGER

Optimus: Accelerating Large-Scale Multi-Modal LLM Training by Bubble Exploitation

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2408.03505.

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

pith.paper-citation-record.v1
2408.03505 v2

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 2026-08-15T06:32:42.880941+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:59:01.645340Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T21:15:09.527296Z

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 b0651ea7-406e-4565-90e6-fb4b1d4a1179 · inbound

Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey cites this paper.

Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey Optimus: Accelerating Large-Scale Multi-Modal LLM Training by Bubble Exploitation

Reference 117

Resolution: unresolved; no resolver link, observed 2026-08-11T14:59:01.645340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d5e525b-ed90-47ac-82d3-b0b222cb023c · inbound

MegaScale-Data: Scaling Dataloader for Multisource Large Foundation Model Training cites this paper.

MegaScale-Data: Scaling Dataloader for Multisource Large Foundation Model Training Optimus: Accelerating Large-Scale Multi-Modal LLM Training by Bubble Exploitation

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-22T21:15:09.530407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bfdebabc-c4ea-45fd-ad31-39e70d3dfba5 · inbound

Seed1.5-VL Technical Report cites this paper.

Seed1.5-VL Technical Report Optimus: Accelerating Large-Scale Multi-Modal LLM Training by Bubble Exploitation

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:26:05.608208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation dddb6e68-f365-494c-af62-c76125f32347 · inbound

Efficient Scaling of LLM Training with Flexible Context Parallelism cites this paper.

Efficient Scaling of LLM Training with Flexible Context Parallelism Optimus: Accelerating Large-Scale Multi-Modal LLM Training by Bubble Exploitation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T20:59:24.588381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ff68390-a53a-46ff-8dae-1d5f36b13d7a · inbound

MegaScale-Omni: A Hyper-Scale, Workload-Resilient System for MultiModal LLM Training in Production cites this paper.

MegaScale-Omni: A Hyper-Scale, Workload-Resilient System for MultiModal LLM Training in Production Optimus: Accelerating Large-Scale Multi-Modal LLM Training by Bubble Exploitation

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:06:14.959042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 825586ba-e448-4ce6-966a-876dd97b1308 · inbound

A Readiness-Driven Runtime for Pipeline-Parallel Training under Runtime Variability cites this paper.

A Readiness-Driven Runtime for Pipeline-Parallel Training under Runtime Variability Optimus: Accelerating Large-Scale Multi-Modal LLM Training by Bubble Exploitation

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:38:09.424255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.