Paper Citation Record · LEDGER

M6: A Chinese Multimodal Pretrainer

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2103.00823.

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

pith.paper-citation-record.v1
2103.00823 v4

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

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:33:38.066200Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T12:14:26.627052Z

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 3f8851c0-dbbc-416f-9e39-fb38c754b508 · inbound

Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model cites this paper.

Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model M6: A Chinese Multimodal Pretrainer

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-24T12:14:26.631436Z

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 150afee1-1804-4672-9037-75b7b00aa375 · inbound

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models cites this paper.

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models M6: A Chinese Multimodal Pretrainer

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:50:12.821851Z

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 a0b41b6b-0463-45dc-95fe-0d0a4706aba5 · inbound

Text-to-Image Synthesis: A Decade Survey cites this paper.

Text-to-Image Synthesis: A Decade Survey M6: A Chinese Multimodal Pretrainer

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-12T13:33:38.066200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cac86b8-bbc0-40f9-9c2d-b4567d4f23b0 · inbound

RepVideo: Rethinking Cross-Layer Representation for Video Generation cites this paper.

RepVideo: Rethinking Cross-Layer Representation for Video Generation M6: A Chinese Multimodal Pretrainer

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T20:16:58.632049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 667e659b-ecd9-4005-aa56-267103e95871 · inbound

Representation Discrepancy Bridging Method for Remote Sensing Image-Text Retrieval cites this paper.

Representation Discrepancy Bridging Method for Remote Sensing Image-Text Retrieval M6: A Chinese Multimodal Pretrainer

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:59:40.772190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f59e01e3-c086-4d29-817c-006b0d1542c6 · inbound

Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned cites this paper.

Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned M6: A Chinese Multimodal Pretrainer

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T22:55:28.493031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5aad8ab-b82c-4816-89e0-6987c51d71d6 · 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: A Chinese Multimodal Pretrainer

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:31:16.889390Z

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 3478a0dc-58d4-4ae1-bcaf-5dc5b91b53f2 · 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: A Chinese Multimodal Pretrainer

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T05:21:30.508049Z

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.