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Paper Citation Record · LEDGER

Small Language Models are Good Too: An Empirical Study of Zero-Shot Classification

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.11122.

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

pith.paper-citation-record.v1
2404.11122 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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:57:59.239773Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T15:57:59.650446Z

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 3b99c89b-e464-4028-a4ac-6e796a9dc4a8 · inbound

Adaptable Embeddings Network (AEN) cites this paper.

Adaptable Embeddings Network (AEN) Small Language Models are Good Too: An Empirical Study of Zero-Shot Classification

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-12T15:57:59.654964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-12T15:57:59.239773Z digest=sha256:8d425aba37f13acb81b9b2bf3497b157f2969ea0994737567cf1a2071ead5e0d

Observation 20891b2e-6ec9-4627-b6bb-e4cfd5fa0d4c · inbound

SLMs as Multi-Agent Routers: A Progressive SFT and Reinforcement Learning Approach cites this paper.

SLMs as Multi-Agent Routers: A Progressive SFT and Reinforcement Learning Approach Small Language Models are Good Too: An Empirical Study of Zero-Shot Classification

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-04T01:47:05.758277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T01:47:05.758277Z digest=sha256:a925feb2aa0f6b2cd8dc9e4c6f4cf4bf28244d5ee1bf417ecf11f568b475d717