Pith. sign in

Paper Citation Record · LEDGER

Challenges and Contributing Factors in the Utilization of Large Language Models (LLMs)

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.13343.

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

pith.paper-citation-record.v1
2310.13343 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 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:49:55.592234Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T04:08:24.531678Z

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 dbb0ff32-3772-4793-abbf-b258c25e7778 · inbound

A RAG-Based Multi-Agent LLM System for Natural Hazard Resilience and Adaptation cites this paper.

A RAG-Based Multi-Agent LLM System for Natural Hazard Resilience and Adaptation Challenges and Contributing Factors in the Utilization of Large Language Models (LLMs)

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-16T10:49:55.592234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:49:55.592234Z digest=sha256:f2c50dded04190bc9b663acff13a0b823374ed2f0fa7937e26c8f85e71dce40d

Observation 73532de9-eaa0-4e47-95b8-86de835abe1e · inbound

A Synergistic Framework of Nonlinear Acoustic Computing and Reinforcement Learning for Real-World Human-Robot Interaction cites this paper.

A Synergistic Framework of Nonlinear Acoustic Computing and Reinforcement Learning for Real-World Human-Robot Interaction Challenges and Contributing Factors in the Utilization of Large Language Models (LLMs)

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-16T04:08:24.556270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T04:08:24.157212Z digest=sha256:80fa7b998f8670d483d85cd27259aea2221e1014156524552560dc75c30e1c89