Paper Citation Record · LEDGER

Contrastive Search Is What You Need For Neural Text Generation

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2210.14140.

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

pith.paper-citation-record.v1
2210.14140 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:19:39.639307Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T05:10:39.763446Z

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 1f2f306c-38f2-4a96-996d-41e2b8bd4a12 · inbound

Improving Linguistic Diversity of Large Language Models with Possibility Exploration Fine-Tuning cites this paper.

Improving Linguistic Diversity of Large Language Models with Possibility Exploration Fine-Tuning Contrastive Search Is What You Need For Neural Text Generation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T22:34:22.698266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5f8d0ae-97e8-4404-9c06-8aad077ed07f · inbound

Context-Enhanced Contrastive Search for Improved LLM Text Generation cites this paper.

Context-Enhanced Contrastive Search for Improved LLM Text Generation Contrastive Search Is What You Need For Neural Text Generation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T11:19:39.639307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 396b9d9c-d248-4e5e-9170-a755796b90c2 · inbound

The Devil is in the EOS: Sequence Training for Detailed Image Captioning cites this paper.

The Devil is in the EOS: Sequence Training for Detailed Image Captioning Contrastive Search Is What You Need For Neural Text Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T17:54:07.442672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca5ab1e6-3db5-44f2-8b24-6eb1b8ec1d43 · inbound

Geometry-Aware Decoding with Wasserstein-Regularized Truncation and Mass Penalties for Large Language Models cites this paper.

Geometry-Aware Decoding with Wasserstein-Regularized Truncation and Mass Penalties for Large Language Models Contrastive Search Is What You Need For Neural Text Generation

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-16T05:10:39.767556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 766b00a8-6cee-4aa5-9eee-16ea9929d1cf · inbound

APCD: Adaptive Path-Contrastive Decoding for Reliable Large Language Model Generation cites this paper.

APCD: Adaptive Path-Contrastive Decoding for Reliable Large Language Model Generation Contrastive Search Is What You Need For Neural Text Generation

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:26:25.240097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 53148b22-d5be-42b7-babe-e497cecce9d8 · inbound

Partition, Prompt, Aggregate: Statistical Self-Consistency in Language Models cites this paper.

Partition, Prompt, Aggregate: Statistical Self-Consistency in Language Models Contrastive Search Is What You Need For Neural Text Generation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T23:43:05.331636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.