Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T10:32:00.603132Z
Paper Citation Record · LEDGER
Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal
As of 15 August 2026, this Paper Citation Record lists 3 of 3 outbound references and 0 inbound Pith citation observations for arXiv:2601.09886.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
3 of 3 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved3
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 5296a9e5-9b58-4d88-b132-2328a4f22b37 · outbound
This paper cites To model human linguistic prediction, make LLMs less superhuman.
Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal To model human linguistic prediction, make LLMs less superhuman
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T10:32:00.404777Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e5298857-4db2-4a5b-9c8a-3d77797abdd1 · outbound
This paper cites InFindings of the Associ- ation for Computational Linguistics: EMNLP 2023, pages 15711–15721.
Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal InFindings of the Associ- ation for Computational Linguistics: EMNLP 2023, pages 15711–15721
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T10:32:00.603132Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fee8eb22-e7b5-4a5a-a5c1-27678ce4c655 · outbound
This paper cites Large-scale cloze evaluation reveals that token prediction tasks are neither lexically nor semantically aligned.
Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal Large-scale cloze evaluation reveals that token prediction tasks are neither lexically nor semantically aligned
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T10:32:00.308547Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.