Paper Citation Record · LEDGER

Language Models for Text Classification: Is In-Context Learning Enough?

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2403.17661.

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

pith.paper-citation-record.v1
2403.17661 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:44:40.199124Z

measured 0 of 1 external citation measurements

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 9d4b1e02-7d2b-430a-90d8-16b5260f8d0b · inbound

Data Quality Enhancement on the Basis of Diversity with Large Language Models for Text Classification: Uncovered, Difficult, and Noisy cites this paper.

Data Quality Enhancement on the Basis of Diversity with Large Language Models for Text Classification: Uncovered, Difficult, and Noisy Language Models for Text Classification: Is In-Context Learning Enough?

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:29.990886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73ab00a2-eb58-47ea-a838-7ef62dd576ef · inbound

Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning cites this paper.

Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning Language Models for Text Classification: Is In-Context Learning Enough?

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:13.450311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8922631-636f-4022-b811-d3a4dcf3555d · inbound

How well can LLMs Grade Essays in Arabic? cites this paper.

How well can LLMs Grade Essays in Arabic? Language Models for Text Classification: Is In-Context Learning Enough?

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T12:46:06.479179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d75b4cda-50a4-4b0b-9b07-f1be791149a3 · inbound

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals cites this paper.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Language Models for Text Classification: Is In-Context Learning Enough?

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T19:44:40.199124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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