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Paper Citation Record · LEDGER

Jointly Training Large Autoregressive Multimodal Models

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.15564.

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

pith.paper-citation-record.v1
2309.15564 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T02:48:44.900467Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T02:48:45.050689Z

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 8da64dc5-3854-49b7-b64f-92c65355871a · inbound

A Survey on Multimodal Large Language Models cites this paper.

A Survey on Multimodal Large Language Models Jointly Training Large Autoregressive Multimodal Models

Reference 150

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T02:56:41.974854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-16T02:56:41.658658Z digest=sha256:dca6b1afdc23e08f246b8645daf5bb928245a4ea786cecd670beb09f79b4356d

Observation 4505b17c-6b11-4056-8c18-46ef0625ef0c · inbound

World Model on Million-Length Video And Language With Blockwise RingAttention cites this paper.

World Model on Million-Length Video And Language With Blockwise RingAttention Jointly Training Large Autoregressive Multimodal Models

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T06:36:57.192118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-16T06:36:57.165551Z digest=sha256:c7cd399d55170cac25cca86a52ec6e21ae16183497679595d71308c2f9b6131e

Observation b0f46758-28f4-40c3-a7a9-22b78f9e9440 · inbound

Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models cites this paper.

Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models Jointly Training Large Autoregressive Multimodal Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-18T02:48:45.053857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-18T02:48:44.900467Z digest=sha256:b7663e8fdbc1f1b1fc676cff1ec78ad20febd13413180b6bae3af2b0c86912c0