Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Adapting Large Language Models for Document-Level Machine Translation
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2401.06468.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T11:43:38.703849Z
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 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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+00:00.