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Paper Citation Record · LEDGER

In-context Examples Selection for Machine Translation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2212.02437.

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

pith.paper-citation-record.v1
2212.02437 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:09:42.234982Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

17
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8819fcee-5465-465a-8aeb-4d61825cec18 · inbound

Dictionary Insertion Prompting for Multilingual Reasoning on Multilingual Large Language Models cites this paper.

Dictionary Insertion Prompting for Multilingual Reasoning on Multilingual Large Language Models In-context Examples Selection for Machine Translation

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-23T18:05:44.786771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-23T18:03:19.212619Z digest=sha256:8f40cc017b892c4e8253f85570f0e8ca1047257c58ec65d55f31161ccfdfc3c7

Observation cf5339df-b526-43a3-8924-5dd81d0268a2 · inbound

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning cites this paper.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning In-context Examples Selection for Machine Translation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T15:09:42.234982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:09:42.234982Z digest=sha256:483382f14db984e3345ac35100c0ee21cafb2cde92fe8978f48cc4a5e4ead6bb

Observation 55f3c3fa-ee0e-47c9-81c5-31d07083d98f · inbound

Mutarjim: Advancing Bidirectional Arabic-English Translation with a Small Language Model cites this paper.

Mutarjim: Advancing Bidirectional Arabic-English Translation with a Small Language Model In-context Examples Selection for Machine Translation

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T14:41:28.993382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:41:28.993382Z digest=sha256:3ab1f6c156f5a5b46e696a5dee86744f67aae621ff25247af630b3a32cb56467

Observation 652c34b6-e9c7-4467-8df9-da098980860b · inbound

SLoW: Select Low-frequency Words! Automatic Dictionary Selection for Translation on Large Language Models cites this paper.

SLoW: Select Low-frequency Words! Automatic Dictionary Selection for Translation on Large Language Models In-context Examples Selection for Machine Translation

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-21T23:34:26.446647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-21T23:31:58.225436Z digest=sha256:0dde640b8e3d35905016ffd35dc725a6ff41be943ea0ccc23d0734b3403f613b

Observation 6a64f11b-f352-413e-8dce-d510434d0d57 · inbound

Failures Are the Stepping Stones to Success: Enhancing Few-Shot In-Context Learning by Leveraging Negative Samples cites this paper.

Failures Are the Stepping Stones to Success: Enhancing Few-Shot In-Context Learning by Leveraging Negative Samples In-context Examples Selection for Machine Translation

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T11:01:54.431180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:01:54.431180Z digest=sha256:f85ab35c8294fd8ed22a630165f1dd7b12bc8a81dcbad1c5e9d82fb5b9e632db