Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Language Models for Text Classification: Is In-Context Learning Enough?
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.17661.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:37:23.227762Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-17T01:33:49.099624Z
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 927dc41a-6b79-4579-bf40-179ae13a3bcf · inbound
From Domain Documents to Requirements: Retrieval-Augmented Generation in the Space Industry cites this paper.
From Domain Documents to Requirements: Retrieval-Augmented Generation in the Space Industry Language Models for Text Classification: Is In-Context Learning Enough?
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:37:23.227762Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae023fff-84ce-4eba-87da-eb7a52a47449 · inbound
A Multi-Stage Large Language Model Framework for Extracting Suicide-Related Social Determinants of Health cites this paper.
A Multi-Stage Large Language Model Framework for Extracting Suicide-Related Social Determinants of Health Language Models for Text Classification: Is In-Context Learning Enough?
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T23:42:37.756235Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation acb86dca-52e3-467c-ad8f-4cf9ba9128d2 · inbound
From scratch to silver: Creating trustworthy training data for patent-SDG classification using Large Language Models cites this paper.
From scratch to silver: Creating trustworthy training data for patent-SDG classification using Large Language Models Language Models for Text Classification: Is In-Context Learning Enough?
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T19:27:04.683699Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b77a5cf0-b58b-43e7-afd8-510da2346f21 · inbound
Poodle: Seamlessly Scaling Down Large Language Models with Just-in-Time Model Replacement cites this paper.
Poodle: Seamlessly Scaling Down Large Language Models with Just-in-Time Model Replacement Language Models for Text Classification: Is In-Context Learning Enough?
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T01:33:49.102114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1c78304c-9f97-4c19-b173-445e8a3e264c · inbound
Measuring Cognitive Engagement in Collaborative Discourse with an Extended ICAP Framework: Comparing Human Annotation, In-Context Learning, and Reflective LLM Agents cites this paper.
Measuring Cognitive Engagement in Collaborative Discourse with an Extended ICAP Framework: Comparing Human Annotation, In-Context Learning, and Reflective LLM Agents Language Models for Text Classification: Is In-Context Learning Enough?
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T00:52:52.018480Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.