Paper Citation Record · LEDGER

What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.04289.

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

pith.paper-citation-record.v1
2406.04289 v5

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 2026-08-12T17:04:34.302293Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:54:37.958204Z

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 63b04910-911c-4973-9d01-00d072fe3c52 · inbound

Training Bilingual LMs with Data Constraints in the Targeted Language cites this paper.

Training Bilingual LMs with Data Constraints in the Targeted Language What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T17:04:34.302293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a45e671c-63d7-4195-bdc0-8ce0d543e64f · inbound

Randomly Sampled Language Reasoning Problems Elucidate Limitations of In-Context Learning cites this paper.

Randomly Sampled Language Reasoning Problems Elucidate Limitations of In-Context Learning What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T22:10:33.867385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c56c51bb-5b0d-43ec-90b7-c497603e32bb · inbound

Information Locality as an Inductive Bias for Neural Language Models cites this paper.

Information Locality as an Inductive Bias for Neural Language Models What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T10:33:01.004820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4263cebb-4060-4b65-896b-2de9b439bc5a · inbound

Rethinking Memorization Measures and their Implications in Large Language Models cites this paper.

Rethinking Memorization Measures and their Implications in Large Language Models What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:54:37.963182Z

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.