Paper Citation Record · LEDGER

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan

As of 11 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2606.09767.

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

pith.paper-citation-record.v1
2606.09767 v1

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T16:20:46.642433Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

10 of 10 outbound references displayed

verified exact1
verified fuzzy0
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b91db2eb-25f1-4e7f-9397-37c408710d3d · outbound

This paper cites 2980–2988 (2017).

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan 2980–2988 (2017)

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-27T16:20:46.642433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae38762e-8508-4394-bf0c-1c6d050dbab7 · outbound

This paper cites mT5: A massively multilingual pre-trained text-to-text transformer.

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan mT5: A massively multilingual pre-trained text-to-text transformer

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T01:47:31.224479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cf4a4e6e-cdfd-4921-80f0-ea103bd99a07 · outbound

This paper cites Scaling neural machine translation to 200 languages.

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan Scaling neural machine translation to 200 languages

Reference 3

Resolution: metadata mismatch; doi, observed 2026-06-27T16:21:01.228611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f438c66e-0e90-466e-a58f-ccd206faba47 · outbound

This paper cites In: Proceedings of the Joint 25th Nordic Conference on Computa- tional Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025), pp.

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan In: Proceedings of the Joint 25th Nordic Conference on Computa- tional Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025), pp

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-27T16:20:46.642433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ab04a11-58cc-4cf2-b169-6a704c78f2e8 · outbound

This paper cites In: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pp.

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan In: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pp

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-27T16:20:46.642433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa0cfc93-729b-4f59-88bf-46c3648bac88 · outbound

This paper cites In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024).

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-27T16:20:46.642433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce5bb5a7-a84d-43a9-824d-893a89250bc9 · outbound

This paper cites arXiv preprint arXiv:2510.13854 (2025).

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan arXiv preprint arXiv:2510.13854 (2025)

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-27T16:21:01.235584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f75d6b34-756b-4752-b530-c7593e311cde · outbound

This paper cites Mayan Languages Preser- vation Project.

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan Mayan Languages Preser- vation Project

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-27T16:20:46.642433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03a0a730-1fce-4f59-afa8-8f5f6a037382 · outbound

This paper cites In: Proceedings of the Third Conference on Machine Translation: Research Papers, pp.

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan In: Proceedings of the Third Conference on Machine Translation: Research Papers, pp

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-27T16:20:46.642433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23cbf24c-7f51-4ba0-9d84-368ae6201f82 · outbound

This paper cites Manning, Joakim Nivre, and Daniel Zeman.

Data Synthesis and Parameter-Efficient Fine-Tuning for Low-Resource NMT: A Case Study on Q'eqchi' Mayan Manning, Joakim Nivre, and Daniel Zeman

Reference 10

Resolution: metadata mismatch; doi, observed 2026-06-27T16:21:01.231814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

No inbound Pith citation observations are available.