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Paper Citation Record · LEDGER

Extrapolating Large Language Models to Non-English by Aligning Languages

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2308.04948.

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

pith.paper-citation-record.v1
2308.04948 v2

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 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:02:26.562644Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:57:09.908959Z

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 0c53ebff-8d24-4020-946a-372be6da4c49 · inbound

CC-Tuning: A Cross-Lingual Connection Mechanism for Improving Joint Multilingual Supervised Fine-Tuning cites this paper.

CC-Tuning: A Cross-Lingual Connection Mechanism for Improving Joint Multilingual Supervised Fine-Tuning Extrapolating Large Language Models to Non-English by Aligning Languages

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T12:02:26.562644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:02:26.562644Z digest=sha256:e286939a25f6b8a3fabb7efb1a1ca0bcb5cab9c11da3994284f4b6055d10d244

Observation b436da42-e246-46a3-ba85-fdfbb031bab3 · inbound

Facts Do Care About Your Language: Assessing Answer Quality of Multilingual LLMs cites this paper.

Facts Do Care About Your Language: Assessing Answer Quality of Multilingual LLMs Extrapolating Large Language Models to Non-English by Aligning Languages

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T11:13:41.054152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:13:41.054152Z digest=sha256:ac72c34920164c83365cc40116277b36830d04f2555c84e1b4f77f631e1c0bc4

Observation b964a25e-4a1b-4914-832a-d5423bccdf05 · inbound

TokAlign: Efficient Vocabulary Adaptation via Token Alignment cites this paper.

TokAlign: Efficient Vocabulary Adaptation via Token Alignment Extrapolating Large Language Models to Non-English by Aligning Languages

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T11:06:28.319125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:06:28.319125Z digest=sha256:4ebb5f5e6ec9efeed714bd3327402f60a5c1650c7c0b859061d0c2b9dc5ccc23

Observation ff83a1c7-1e72-4647-b431-9ee89ffb44e5 · inbound

Text2Cypher Across Languages: Evaluating and Finetuning LLMs cites this paper.

Text2Cypher Across Languages: Evaluating and Finetuning LLMs Extrapolating Large Language Models to Non-English by Aligning Languages

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T22:28:15.666333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:28:15.666333Z digest=sha256:6ca13f2611861df97443955d8e2dcff46cffe38e657fd20709dfde99569742d9

Observation 6d5c6de7-8506-4652-b53b-15d7be5c70a7 · inbound

M-DaQ: Retrieving Samples with Multilingual Diversity and Quality for Instruction Fine-Tuning Datasets cites this paper.

M-DaQ: Retrieving Samples with Multilingual Diversity and Quality for Instruction Fine-Tuning Datasets Extrapolating Large Language Models to Non-English by Aligning Languages

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-18T16:46:37.548826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T16:45:41.475107Z digest=sha256:20e915e2811e8cd09361fa1c303975668aaa0d92a7b2accd047a9b3ac34bef3e

Observation 34c11d67-4c3c-4f59-ad1c-5c266ed09991 · inbound

The GaoYao Benchmark: A Comprehensive Framework for Evaluating Multilingual and Multicultural Abilities of Large Language Models cites this paper.

The GaoYao Benchmark: A Comprehensive Framework for Evaluating Multilingual and Multicultural Abilities of Large Language Models Extrapolating Large Language Models to Non-English by Aligning Languages

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:49:48.390517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T00:49:14.664789Z digest=sha256:fe9dd6ba12f900c660f285a444bab84990585486856fee3f8134eba5116efdae

Observation e4d18b47-5044-4a93-9b7a-993bd3a92d13 · inbound

TokAlign++: Advancing Vocabulary Adaptation via Better Token Alignment cites this paper.

TokAlign++: Advancing Vocabulary Adaptation via Better Token Alignment Extrapolating Large Language Models to Non-English by Aligning Languages

Reference 69

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T19:37:52.297282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-14T19:35:10.026293Z digest=sha256:f8516e8ab2eee931eee9f501ce110f87a3589859bc9dabcce01cc7de4c820c6b

Observation 1382dddd-ed81-4c8f-a3bd-c05ff87e8fc4 · inbound

MADE: Beyond Scoring via a Multilingual Agentic Diagnosing Engine for Fine-Grained Evaluation Insights cites this paper.

MADE: Beyond Scoring via a Multilingual Agentic Diagnosing Engine for Fine-Grained Evaluation Insights Extrapolating Large Language Models to Non-English by Aligning Languages

Reference 111

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T16:57:09.910757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T22:16:42.836058Z digest=sha256:c97474e1734771d22ddf6d0e0e3fb4aa32c568365b26ad8576eece63215c543f