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Paper Citation Record · LEDGER

On Decoding Strategies for Neural Text Generators

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2203.15721.

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

pith.paper-citation-record.v1
2203.15721 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:16:27.133877Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T12:43:50.160455Z

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 cfd5b7d9-a356-4d4b-b6c1-95a292c4d163 · inbound

Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs cites this paper.

Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs On Decoding Strategies for Neural Text Generators

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T11:16:27.133877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:16:27.133877Z digest=sha256:0e0cb3410e5c7f98c57e5254085530dddda383817816c711d16ae74ab04ab849

Observation 71ee6770-dca1-486a-8711-a7eb0cb4244d · inbound

Multi-Hypothesis Distillation of Multilingual Neural Translation Models for Low-Resource Languages cites this paper.

Multi-Hypothesis Distillation of Multilingual Neural Translation Models for Low-Resource Languages On Decoding Strategies for Neural Text Generators

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:43:50.230149Z

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=pdf_text observed=2026-08-06T12:43:47.522727Z digest=sha256:61ab1b798ead21e22b9e8fa5534d78a187c216ccd5b3af313737842179e3c7cc