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Paper Citation Record · LEDGER

Multilingual Large Language Models and Curse of Multilinguality

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.10602.

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

pith.paper-citation-record.v1
2406.10602 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:52:27.834797Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T15:01:03.878804Z

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 4354f0a9-961f-4be5-b27d-78afba2db335 · inbound

SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use cites this paper.

SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use Multilingual Large Language Models and Curse of Multilinguality

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:52:27.834797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:52:27.834797Z digest=sha256:9ff9122a3fea58356e233107e62f87beffd6a015c3c3ce78efcea9bea9fc2b67

Observation 5990c254-2e27-422a-a56c-c54b477ebed6 · inbound

TreeReview: A Dynamic Tree of Questions Framework for Deep and Efficient LLM-based Scientific Peer Review cites this paper.

TreeReview: A Dynamic Tree of Questions Framework for Deep and Efficient LLM-based Scientific Peer Review Multilingual Large Language Models and Curse of Multilinguality

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T05:33:21.263525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:33:21.263525Z digest=sha256:285eb734612360a0360914d9b105aa90aeb7fa94b5b484987b741ce2adf2a348

Observation aba52b27-f523-4845-885f-ddbf827b837b · inbound

The Roots of Performance Disparity in Multilingual Language Models: Intrinsic Modeling Difficulty or Design Choices? cites this paper.

The Roots of Performance Disparity in Multilingual Language Models: Intrinsic Modeling Difficulty or Design Choices? Multilingual Large Language Models and Curse of Multilinguality

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-16T15:01:03.881775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-16T14:59:02.533789Z digest=sha256:9f135009e6e9f814296dea96c785e2f3396d1584d93f23d99226fb429a7ce7c8

Observation ea2d9432-442c-4044-b47f-c0cc1eea0484 · inbound

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition cites this paper.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Multilingual Large Language Models and Curse of Multilinguality

Reference 2012

Resolution
unresolved
no resolver link, observed 2026-07-31T23:18:46.840026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:18:46.840026Z digest=sha256:2d8a5e504ca35b5850e659701b798a696c143da488411e4b7be821c6da1d7653