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Paper Citation Record · LEDGER

Simple Linguistic Inferences of Large Language Models (LLMs): Blind Spots and Blinds

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.14785.

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

pith.paper-citation-record.v1
2305.14785 v2

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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:48:02.107085Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T11:29:21.933856Z

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 dc17bebf-520d-4074-9938-071487f424f5 · inbound

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives cites this paper.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Simple Linguistic Inferences of Large Language Models (LLMs): Blind Spots and Blinds

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-09T11:29:21.939327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.046165Z digest=sha256:97edf8345c82d3b1a2449f4e1d2335a3568da5bbc081e2033eab2f426b496a36

Observation 90c596d1-adaa-4d26-98eb-cc287ac60f04 · inbound

For GPT-4 as with Humans: Information Structure Predicts Acceptability of Long-Distance Dependencies cites this paper.

For GPT-4 as with Humans: Information Structure Predicts Acceptability of Long-Distance Dependencies Simple Linguistic Inferences of Large Language Models (LLMs): Blind Spots and Blinds

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T21:48:02.107085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:48:02.107085Z digest=sha256:dc8b8b772fcdd646156edbeeaa3014fba292596b446922ec0f38682bcd8e3a0d