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Paper Citation Record · LEDGER

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation

As of 10 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2607.26286.

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

pith.paper-citation-record.v1
2607.26286 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T00:17:56.362668Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

20 of 20 outbound references displayed

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  • verified fuzzy0
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9e3898d4-7533-4935-84d7-2adaeab8955e · outbound

This paper cites an unresolved cited work.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Unresolved cited work

Reference 1

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no resolver link, observed 2026-08-01T00:17:53.482624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c837fc59-cadb-495f-84a1-3b630cd5809c · outbound

This paper cites Translating Terminological Expressions in Knowledge Bases with Neural Machine Translation.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Translating Terminological Expressions in Knowledge Bases with Neural Machine Translation

Reference 2

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:53.600015Z digest=sha256:0d3ede311f545aef25efde3f43b808c46e4f92ee70d83eb8420b917d2b758b11

Observation e05766e8-a89e-40ce-9546-17fd25d2b363 · outbound

This paper cites Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al

Reference 3

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no resolver link, observed 2026-08-01T00:17:53.728484Z

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Unavailable: canonical work link unavailable.

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Observation 4ac38a4d-6796-40d4-9f70-761947136a78 · outbound

This paper cites an unresolved cited work.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Unresolved cited work

Reference 4

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no resolver link, observed 2026-08-01T00:17:53.836895Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:53.836895Z digest=sha256:91802b5f317dd9505c551ee6fb2821fbdb43c40547098d1519b925a7241791e6

Observation 317ddf2a-4ed2-4a68-836f-00b3fc893e27 · outbound

This paper cites Enhancing translation quality by leveraging semantic diversity in multimodal machine translation.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Enhancing translation quality by leveraging semantic diversity in multimodal machine translation

Reference 5

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:53.964956Z digest=sha256:b9bc828d01f2a08f2ad535c70694a233c2feb64d658e01d57c9a629033673ae1

Observation 399b1f58-c927-48c5-abf8-9bab9d29b081 · outbound

This paper cites How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 6

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no resolver link, observed 2026-08-01T00:17:54.133008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:54.133008Z digest=sha256:21eb205b48ff52fbe7faaa208787f26046409b36489982b2dcf4e3d6ab9efec1

Observation 0891e1ee-ca27-4bd1-a09b-e7377574bf72 · outbound

This paper cites an unresolved cited work.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Unresolved cited work

Reference 7

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no resolver link, observed 2026-08-01T00:17:54.300860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:54.300860Z digest=sha256:e9cff7e80bc036f42a9699af4ff6d1c66c554a5e358b76b7924aaeb86129b72c

Observation c06aa4ad-a693-437b-93a7-a37bd199ee4d · outbound

This paper cites What makes good in-context examples for GPT-3? InProceedings of Deep Learning Inside Out, pages 100–114.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation What makes good in-context examples for GPT-3? InProceedings of Deep Learning Inside Out, pages 100–114

Reference 8

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no resolver link, observed 2026-08-01T00:17:54.468933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 34ca7fc1-7a22-434d-9932-7497eb20bdbc · outbound

This paper cites McCrae, Mihael Arcan, and Paul Buitelaar.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation McCrae, Mihael Arcan, and Paul Buitelaar

Reference 9

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no resolver link, observed 2026-08-01T00:17:54.625672Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:54.625672Z digest=sha256:01555ad9a96afd6a4a0d7e485bc46497f5e5a998ceeac5ad45c0a17c4075ffad

Observation 02651229-b900-4c43-afd1-5fd83d2b02d5 · outbound

This paper cites No Language Left Behind: Scaling Human-Centered Machine Translation.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation No Language Left Behind: Scaling Human-Centered Machine Translation

Reference 10

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no resolver link, observed 2026-08-01T00:17:54.747705Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:54.747705Z digest=sha256:7eea3a8682073843e766279b884b10573768edbd2743a428149db3d3a2f888eb

Observation eafb7050-112f-46d8-a9cb-7746a921b2a6 · outbound

This paper cites chrF: Character n-gram F-score for automatic MT evaluation.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation chrF: Character n-gram F-score for automatic MT evaluation

Reference 11

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Unavailable: canonical work link unavailable.

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Observation bac16c40-9997-442c-9268-e9762df06378 · outbound

This paper cites chrF++: Words helping character n-grams.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation chrF++: Words helping character n-grams

Reference 12

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no resolver link, observed 2026-08-01T00:17:55.134630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c00c24a6-1002-40a8-8c18-6a6126d4f86e · outbound

This paper cites A call for clarity in reporting BLEU scores.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation A call for clarity in reporting BLEU scores

Reference 13

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Unavailable: canonical work link unavailable.

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Observation 9d0fc886-f71e-4f3b-a43f-f363e141e942 · outbound

This paper cites an unresolved cited work.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Unresolved cited work

Reference 14

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no resolver link, observed 2026-08-01T00:17:55.487394Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:55.487394Z digest=sha256:6d6241dda36321192c25b72f0d48ef2659a69b0db0089d47163a592d52c54d4e

Observation 1732ccc7-ac78-42c5-b5ef-09fc71ab3d53 · outbound

This paper cites Farinha, and Alon Lavie.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Farinha, and Alon Lavie

Reference 15

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:55.704846Z digest=sha256:86449a6ae754c30f3f37d8502bf2c08a386539b0c26761e2af8acbf299ebbd07

Observation ced77799-e168-4f35-be69-ccf6fa11c00b · outbound

This paper cites The OPUS-MT project: Building open translation services for the world.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation The OPUS-MT project: Building open translation services for the world

Reference 16

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no resolver link, observed 2026-08-01T00:17:55.927686Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:55.927686Z digest=sha256:39d15336ed81e33e884475b5a8e6331439c79b9c4824b4ad7f7d5c6553a18d76

Observation fad32a1a-e796-4b75-bffc-5a27fe3351cc · outbound

This paper cites Leveraging rule-based machine translation knowledge for under-resourced neural machine translation models.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Leveraging rule-based machine translation knowledge for under-resourced neural machine translation models

Reference 17

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no resolver link, observed 2026-08-01T00:17:56.093097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation af2b13ac-4f9d-4b8a-8c47-8f96fc4ed42e · outbound

This paper cites Aspects of Terminological and Named Entity Knowledge within Rule-Based Machine Translation Models for Under-Resourced Neural Machine Translation Scenarios.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Aspects of Terminological and Named Entity Knowledge within Rule-Based Machine Translation Models for Under-Resourced Neural Machine Translation Scenarios

Reference 18

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Unavailable: canonical work link unavailable.

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Observation ff9576d1-23ef-4feb-ae88-e8df7371eb0a · outbound

This paper cites Prompting Large Language Model for Machine Translation: A Case Study.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Prompting Large Language Model for Machine Translation: A Case Study

Reference 19

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Unavailable: canonical work link unavailable.

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Observation e489a2be-0756-4f31-843c-a09d4f581003 · outbound

This paper cites an unresolved cited work.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation Unresolved cited work

Reference 2015

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no resolver link, observed 2026-08-01T00:17:55.027717Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:17:55.027717Z digest=sha256:82f100e84d9a5ede45f054bef5f6c086643c675115a929ea1d992f36870755d3

Pith citing papers

No inbound Pith citation observations are available.