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Paper Citation Record · LEDGER

Are Small Language Models Ready to Compete with Large Language Models for Practical Applications?

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.11402.

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

pith.paper-citation-record.v1
2406.11402 v3

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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:30:44.786694Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T22:41:53.998388Z

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 0dab1863-5e52-47b6-b4f2-c1731dfdb6e7 · inbound

VocabTailor: Dynamic Vocabulary Selection for Downstream Tasks in Small Language Models cites this paper.

VocabTailor: Dynamic Vocabulary Selection for Downstream Tasks in Small Language Models Are Small Language Models Ready to Compete with Large Language Models for Practical Applications?

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:41:54.001982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-18T22:37:01.014698Z digest=sha256:36d052766652e870384634220b26e78d5e05b64e6a41aa11869a546ea97a3690

Observation e7ba0a9e-6f2d-4c4d-8f37-5f258d600510 · inbound

Agentic LLMs for Question Answering over Tabular Data cites this paper.

Agentic LLMs for Question Answering over Tabular Data Are Small Language Models Ready to Compete with Large Language Models for Practical Applications?

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.786694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.786694Z digest=sha256:443c2e15204235af769a81e60859a459920e54b9774c9acb089a4688ad07bf9d