Paper Citation Record · LEDGER

Adapting Large Language Models for Document-Level Machine Translation

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2401.06468.

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

pith.paper-citation-record.v1
2401.06468 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:44:49.193524Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:57:09.911154Z

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 93006335-1633-4f61-92a2-dedc342e9ce0 · inbound

Proverbs Run in Pairs: Evaluating Proverb Translation Capability of Large Language Model cites this paper.

Proverbs Run in Pairs: Evaluating Proverb Translation Capability of Large Language Model Adapting Large Language Models for Document-Level Machine Translation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T17:44:49.193524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d83ffa62-e3c4-4b64-b1bd-784b353f27d0 · inbound

A comparison of translation performance between DeepL and Supertext cites this paper.

A comparison of translation performance between DeepL and Supertext Adapting Large Language Models for Document-Level Machine Translation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T11:43:38.703849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b77e8426-9534-4e9e-88ba-93c1241fe5aa · inbound

Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translation cites this paper.

Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translation Adapting Large Language Models for Document-Level Machine Translation

Reference 182

Resolution: verified exact; arxiv_id, observed 2026-05-22T21:42:11.269819Z

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 afbf69f7-296f-4109-a4e9-24b7efe00cd2 · inbound

Beyond the Sentence: A Survey on Context-Aware Machine Translation with Large Language Models cites this paper.

Beyond the Sentence: A Survey on Context-Aware Machine Translation with Large Language Models Adapting Large Language Models for Document-Level Machine Translation

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-07T05:33:55.725036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24e69e6d-942c-491c-b54c-ba2d5a66c4e9 · inbound

GRAFT: A Graph-based Flow-aware Agentic Framework for Document-level Machine Translation cites this paper.

GRAFT: A Graph-based Flow-aware Agentic Framework for Document-level Machine Translation Adapting Large Language Models for Document-Level Machine Translation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T20:17:49.777015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1702dcd-5634-49fb-aeb4-e3b02489b405 · inbound

When Prompts Become Payloads: A Framework for Mitigating SQL Injection Attacks in Large Language Model-Driven Applications cites this paper.

When Prompts Become Payloads: A Framework for Mitigating SQL Injection Attacks in Large Language Model-Driven Applications Adapting Large Language Models for Document-Level Machine Translation

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:51:25.121079Z

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 efbf4e70-f290-4c55-96e7-d9c89f1fc486 · inbound

What Does LLM Refinement Actually Improve? A Systematic Study on Document-Level Literary Translation cites this paper.

What Does LLM Refinement Actually Improve? A Systematic Study on Document-Level Literary Translation Adapting Large Language Models for Document-Level Machine Translation

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:09:26.152992Z

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 7817873b-6c22-4330-ba14-8a65d6970d3d · inbound

G^2C-MT: Graph-Guided Context Selection for Document-Level Machine Translation cites this paper.

G^2C-MT: Graph-Guided Context Selection for Document-Level Machine Translation Adapting Large Language Models for Document-Level Machine Translation

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T02:46:29.234281Z

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 e672e89b-0b6e-486d-8640-1c26e49442ee · inbound

MADE: Beyond Scoring via a Multilingual Agentic Diagnosing Engine for Fine-Grained Evaluation Insights cites this paper.

MADE: Beyond Scoring via a Multilingual Agentic Diagnosing Engine for Fine-Grained Evaluation Insights Adapting Large Language Models for Document-Level Machine Translation

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:57:09.912896Z

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 78586609-2061-412c-94eb-18f2e100fbc4 · inbound

Which Tokens Need Context? A Reference-Based Analysis of Translation Responsibility Using Fertility and Entropy cites this paper.

Which Tokens Need Context? A Reference-Based Analysis of Translation Responsibility Using Fertility and Entropy Adapting Large Language Models for Document-Level Machine Translation

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:34:21.355308Z

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.