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Paper Citation Record · LEDGER

Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2501.06346.

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

pith.paper-citation-record.v1
2501.06346 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 2026-08-20T06:33:59.587034+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:58:17.464482Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T02:43:53.144935Z

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 6a5752c2-39a2-4afe-9133-2cc701c7cd3d · inbound

Amplify Initiative: Building A Localized Data Platform for Globalized AI cites this paper.

Amplify Initiative: Building A Localized Data Platform for Globalized AI Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-16T11:58:17.464482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:58:17.464482Z digest=sha256:317b8be716d663b4e6edcff3e492931541a931c15a9e85f277c2c677de132604

Observation 051ef9ac-a2d4-4b48-a5ac-1d69ebca18c1 · inbound

$K$-MSHC: Unmasking Minimally Sufficient Head Circuits in Large Language Models with Experiments on Syntactic Classification Tasks cites this paper.

$K$-MSHC: Unmasking Minimally Sufficient Head Circuits in Large Language Models with Experiments on Syntactic Classification Tasks Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-15T20:41:57.686649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:41:57.686649Z digest=sha256:1f92d48112837640108306a6e0a6abfc24c6502138c36e01febba3225eeb68b9

Observation 25f2f823-ad08-4cdf-b861-469e1730691d · inbound

How Syntax Specialization Emerges in Language Models cites this paper.

How Syntax Specialization Emerges in Language Models Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:58.686767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:17:58.686767Z digest=sha256:cf8fb8778420312e23e6621fe73ec1a49e52b8b9bf5b4d05d13a5a70c945b5c1

Observation e6165b07-a4d8-48ef-87da-5325b538fde3 · inbound

The Emergence of Abstract Thought in Large Language Models Beyond Any Language cites this paper.

The Emergence of Abstract Thought in Large Language Models Beyond Any Language Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T04:43:38.559062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:43:38.559062Z digest=sha256:e708f696f268eee368ba97f6123a2f68c55c0876671cfad9c3c27b8ddf05119e

Observation 28d764f4-31a6-43f0-b9a4-3641c5102472 · inbound

Rethinking Cross-lingual Gaps from a Statistical Viewpoint cites this paper.

Rethinking Cross-lingual Gaps from a Statistical Viewpoint Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-04T09:26:50.088407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:26:50.088407Z digest=sha256:5c900a72dd50c6ed7b13efe1d127de7f1ff529bc3cf0159000e52592c469333f

Observation ef36a3a0-2b85-4efc-8668-55156d373015 · inbound

Different types of syntactic agreement recruit the same units within large language models cites this paper.

Different types of syntactic agreement recruit the same units within large language models Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-17T02:43:53.148933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-17T02:43:51.273343Z digest=sha256:c4446731fd125d2aa7803841d3f839a6e8ea5db4f2c76b228ffcc4c1230a3c36

Observation 6877cada-570a-4928-81b1-1f887febcf19 · inbound

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

Semantic Primes as Explanans for Emotion in Large Language Models Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-01T14:42:15.055990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T14:42:15.055990Z digest=sha256:4775a6eaa645b57d09e5038753f5cae77139973793e27cb46711a886b0bddcdb