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Paper Citation Record · LEDGER

Do Llamas Work in English? On the Latent Language of Multilingual Transformers

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2402.10588.

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

pith.paper-citation-record.v1
2402.10588 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:31:59.899901Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T10:01:27.516206Z

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 7203753f-3149-4d15-bb44-1ec0e10bbe41 · inbound

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation cites this paper.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.899901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.899901Z digest=sha256:1726d598b183c8cca314bc73268d75fa0d3ee084c49cbf3f5fcde9312e67b21d

Observation b6c06667-938c-4c11-8537-408b21d3cae2 · inbound

Paths Not Taken: Understanding and Mending the Multilingual Factual Recall Pipeline cites this paper.

Paths Not Taken: Understanding and Mending the Multilingual Factual Recall Pipeline Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T13:58:19.985179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:58:19.985179Z digest=sha256:4bfe758ff7b4b9b834d2799973b75b94c6313092a234b1dd4deb7db8d1d69631

Observation 2d4d9e63-387f-4f55-9ef2-9ed1152d6fc5 · inbound

Disentangling Language and Culture for Evaluating Multilingual Large Language Models cites this paper.

Disentangling Language and Culture for Evaluating Multilingual Large Language Models Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:32.626946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:32.626946Z digest=sha256:f818525daf767e8440d7b61f430ffbc02c27551a16b1dc2e9c12063bf17b7322

Observation a3f60f49-7ada-42c7-b346-8f17698cb5c9 · inbound

How Programming Concepts and Neurons Are Shared in Code Language Models cites this paper.

How Programming Concepts and Neurons Are Shared in Code Language Models Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T11:56:18.771008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:56:18.771008Z digest=sha256:b45f784033e12645e3fdbc6bc8cf26eb18c0aa0cf6a60ccf27563167e5a4f150

Observation 88c85fa9-2e18-4923-b9b8-f403c0492ea2 · inbound

CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention cites this paper.

CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T11:22:38.901556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:22:38.901556Z digest=sha256:a29fdac277b3b6385bd50b9da9fb5c22f07bb31dba4b9f7262de7ff7fb500e6e

Observation 0343fc5b-0a5b-4893-a932-bfd7ec1bca87 · inbound

BASIC: Boosting Visual Alignment with Intrinsic Refined Embeddings in Multimodal Large Language Models cites this paper.

BASIC: Boosting Visual Alignment with Intrinsic Refined Embeddings in Multimodal Large Language Models Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-05T22:35:50.930906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:35:50.930906Z digest=sha256:0e52a1f74c4c3d45d3cf800bdc8f64dcc823f35ad680ac63337322b383ce0c83

Observation e7b944df-21bb-44d7-ac4b-5c48c10afc26 · inbound

Language-Specific Layer Matters: Efficient Multilingual Enhancement for Large Vision-Language Models cites this paper.

Language-Specific Layer Matters: Efficient Multilingual Enhancement for Large Vision-Language Models Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-05T16:30:12.644110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:30:12.644110Z digest=sha256:87dab9ac37fbea618e2c5cef64cca1304c71bd48a268e22ea0cfbf0686811a5d

Observation c8fe496d-3220-4838-a964-cde4695b6e01 · inbound

Controlling the Risk of Corrupted Contexts for Language Models via Early-Exiting cites this paper.

Controlling the Risk of Corrupted Contexts for Language Models via Early-Exiting Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-04T12:45:26.813263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T12:45:26.813263Z digest=sha256:49f51076d2bcbb933e23dec73a4f6f6e5292c12db261a46de5a414d03bccf305

Observation 77546dbe-5bc2-4420-85a1-4cd65f947bcd · inbound

ChiKhaPo: A Large-Scale Multilingual Benchmark for Evaluating Lexical Comprehension and Generation in Large Language Models cites this paper.

ChiKhaPo: A Large-Scale Multilingual Benchmark for Evaluating Lexical Comprehension and Generation in Large Language Models Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-04T09:11:58.018167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:11:58.018167Z digest=sha256:a250a7845b47548a4c118319f9ea43ac6973d32c6365a4633d37c665f7f70477

Observation 42049a97-7f1d-4f9a-b35a-c3f20a8fc74f · inbound

Perturbation Probing: A Two-Pass-per-Prompt Diagnostic for FFN Behavioral Circuits in Aligned LLMs cites this paper.

Perturbation Probing: A Two-Pass-per-Prompt Diagnostic for FFN Behavioral Circuits in Aligned LLMs Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:01:27.519074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T08:34:14.310656Z digest=sha256:514bfbcb033406a43e94241bac644bc663cee1436157ef5dd1ffeac9e068a978

Observation c0fd1f32-3ce7-4e43-b8e3-675af031c1e1 · inbound

Semantic Primes as Explanans for Emotion in Large Language Models cites this paper.

Semantic Primes as Explanans for Emotion in Large Language Models Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-01T14:42:16.506157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T14:42:16.506157Z digest=sha256:9a6925cf38d1fc474d60fc08e2127362e4d6c666302e35b139f5c2d1e5e4abb4