Paper Citation Record · LEDGER

A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2305.01181.

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

pith.paper-citation-record.v1
2305.01181 v3

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 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:40:58.155884Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T13:24:40.051331Z

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 29fbde0c-9c22-48bb-8c8e-450546b3bfe5 · inbound

Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation cites this paper.

Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T14:40:58.155884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da7635fc-2190-4561-b9c3-f2daa71a078a · inbound

SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use cites this paper.

SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:52:29.088283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 786880a4-3030-46a7-a1e4-1a8e98dd4fad · inbound

Ancient Greek to Modern Greek Machine Translation: A Novel Benchmark and Fine-Tuning Experiments on LLMs and NMT Models cites this paper.

Ancient Greek to Modern Greek Machine Translation: A Novel Benchmark and Fine-Tuning Experiments on LLMs and NMT Models A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T11:18:13.760179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 86d73fc4-849a-416d-bc47-1d3a9a389b4d · inbound

Mix-MoE: Improving Multilingual Machine Translation of Large Language Models through Mixed MoEs cites this paper.

Mix-MoE: Improving Multilingual Machine Translation of Large Language Models through Mixed MoEs A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-30T13:24:40.052918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.