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Paper Citation Record · LEDGER

Multilingual Large Language Models: A Systematic Survey

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2411.11072.

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

pith.paper-citation-record.v1
2411.11072 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:38:18.882563Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0b826cfc-c2cb-4d77-9f7c-3cfa23910ef3 · inbound

A quantitative analysis of semantic information in deep representations of text and images cites this paper.

A quantitative analysis of semantic information in deep representations of text and images Multilingual Large Language Models: A Systematic Survey

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-22T14:41:41.524278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T14:38:08.201470Z digest=sha256:974d7bf4381832fa862488bd8589011fbb586ad1d06da2ed8278fe226e5361d7

Observation 73259d88-f851-4ef2-85d1-b752a93d74be · inbound

From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for Tibetan cites this paper.

From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for Tibetan Multilingual Large Language Models: A Systematic Survey

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-19T04:57:04.358393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-19T04:56:16.979713Z digest=sha256:57d9ae1bd890ea20dacba8a12ce5abc1a7661ac18f8a3b1d1ff33beaa696a215

Observation 3758fbd8-d69e-45f0-a149-634b6a2d5cb0 · inbound

HKGAI-V1: Towards Regional Sovereign Large Language Model for Hong Kong cites this paper.

HKGAI-V1: Towards Regional Sovereign Large Language Model for Hong Kong Multilingual Large Language Models: A Systematic Survey

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T17:38:18.882563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:38:18.882563Z digest=sha256:bffd9219bfe7721ae215eb50e405e79242cd176b28446c9b6a5e039de1033879

Observation dccb1653-7e37-4aff-8044-5805b4604376 · inbound

VisR-Bench: An Empirical Study on Visual Retrieval-Augmented Generation for Multilingual Long Document Understanding cites this paper.

VisR-Bench: An Empirical Study on Visual Retrieval-Augmented Generation for Multilingual Long Document Understanding Multilingual Large Language Models: A Systematic Survey

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-05T22:10:08.255901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:10:08.255901Z digest=sha256:e523802f45221c48f12fc198a3cc7def3d3c91d276d2c246d452df28b79e8ea0

Observation 90a24fe8-89de-462b-a77a-f0e989f96761 · inbound

APPSI-139: A Parallel Corpus of English Application Privacy Policy Summarization and Interpretation cites this paper.

APPSI-139: A Parallel Corpus of English Application Privacy Policy Summarization and Interpretation Multilingual Large Language Models: A Systematic Survey

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T10:01:27.858823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T08:30:14.156832Z digest=sha256:7fd9181877472bd739fab9e9f13f395dd330a81f8fb9afa79ee02d5c5889fd60

Observation 4e66d668-1864-4e08-98cb-af1a7800cd8c · inbound

SARA: Unlocking Multilingual Knowledge in Mixture-of-Experts via Semantically Anchored Routing Alignment cites this paper.

SARA: Unlocking Multilingual Knowledge in Mixture-of-Experts via Semantically Anchored Routing Alignment Multilingual Large Language Models: A Systematic Survey

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T20:00:09.057645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-25T20:48:04.003465Z digest=sha256:042cf324e88ce2589def55cba8ec4d7707a157bdcc2e2b9ee1ba060ab6f366bc

Observation 455b24bf-68bc-4181-a298-8fd080eab083 · inbound

YOMI-Bench: A Benchmark for Evaluating Kanji Reading and Phonological Understanding of LLMs for Japanese cites this paper.

YOMI-Bench: A Benchmark for Evaluating Kanji Reading and Phonological Understanding of LLMs for Japanese Multilingual Large Language Models: A Systematic Survey

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T13:06:58.274241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-07-02T13:03:58.617626Z digest=sha256:23f85264674ceb4036981d5b89a98bbb595a0b44c51a91d142ee4ba5a8fa89b6