Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1903.06059.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:46:41.527668Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-04T14:39:58.282777Z
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 e8976faa-2788-45e4-8397-bb9aa518aac7 · inbound
Variational Prefix Tuning for Diverse and Accurate Code Summarization Using Pre-trained Language Models cites this paper.
Variational Prefix Tuning for Diverse and Accurate Code Summarization Using Pre-trained Language Models Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:46:41.527668Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6cfba2bf-211a-40b7-9a3b-a036a36d592c · inbound
Looking elsewhere: improving variational Monte Carlo gradients by importance sampling cites this paper.
Looking elsewhere: improving variational Monte Carlo gradients by importance sampling Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:37:28.200396Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 153156fe-6048-4ea5-90dc-e0ee17eafe51 · inbound
Efficient Test-Time Inference via Deterministic Exploration of Truncated Decoding Trees cites this paper.
Efficient Test-Time Inference via Deterministic Exploration of Truncated Decoding Trees Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T01:04:50.000321Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0f93ec1b-0866-4357-a7a6-304152e9b1cb · inbound
An Iterative Dual-Channel Neural Quantum State Algorithm for Selected Configuration Interaction cites this paper.
An Iterative Dual-Channel Neural Quantum State Algorithm for Selected Configuration Interaction Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
Reference 39
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T14:39:58.284250Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4f40a9d8-198f-493b-96a4-50da57642f0b · inbound
Rank-Conditioned Sample Reuse for the Plackett--Luce Best-of-$K$ Objective cites this paper.
Rank-Conditioned Sample Reuse for the Plackett--Luce Best-of-$K$ Objective Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T06:44:16.198117Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.