Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2110.03888.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T10:16:09.245076Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T01:07:22.287771Z
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 cdf3becd-21f6-4168-9b75-c5a3413776d3 · 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 M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining
Reference 165
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T01:07:22.289313Z
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.
Observation 59ff5f7a-1151-49fb-9e77-13748d6ceb5d · inbound
An Integrated Framework for Contextual Personalized LLM-Based Food Recommendation cites this paper.
An Integrated Framework for Contextual Personalized LLM-Based Food Recommendation M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining
Reference 113
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:16:09.245076Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1c64c3ed-d511-460e-a6db-c20dfd1dabe7 · inbound
QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration cites this paper.
QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining
Reference 2011
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:45:12.187026Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 945e0245-891f-4d70-8b7a-ab9036e49b01 · inbound
AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.
AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T15:31:17.626282Z
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.
Observation d54c0e61-df97-4609-97d9-7f633cab5ec1 · inbound
AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.
AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T05:21:30.086287Z
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.