Paper Citation Record · LEDGER

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation

As of 21 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2504.17445.

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

pith.paper-citation-record.v1
2504.17445 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:43:18.446845Z

measured 18 of 18 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

verified exact0
verified fuzzy14
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cc51d327-35c5-4988-9525-c626ccd883d9 · outbound

This paper cites Three gaps in computational text analysis methods for social sciences: A research agenda.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Three gaps in computational text analysis methods for social sciences: A research agenda

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.698049Z

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 bc5f469f-517b-4e01-9b3f-36ab2769085b · outbound

This paper cites Druckman.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Druckman

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.685892Z

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 72d133de-56b0-4ff1-b04c-5bbb6fea490a · outbound

This paper cites Keyword-assisted topic models.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Keyword-assisted topic models

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.673847Z

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 20befaf3-8953-46cc-a8a2-0e222157a3ba · outbound

This paper cites Assessing topic model relevance: Evaluation and informative priors.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Assessing topic model relevance: Evaluation and informative priors

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.661402Z

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 b23f49ae-b72b-44a5-854a-17df9167b995 · outbound

This paper cites A bayesian hierarchical topic model for political texts: Measuring expressed agendas in senate press releases.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation A bayesian hierarchical topic model for political texts: Measuring expressed agendas in senate press releases

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.649485Z

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 6ead96f7-56aa-4330-8a24-0cdcec4b6a9f · outbound

This paper cites Text as data: The promise and pitfalls of automatic content analysis methods for political texts.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Text as data: The promise and pitfalls of automatic content analysis methods for political texts

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.637040Z

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 eb20c46c-bebd-4d85-aee4-a1481001ac0c · outbound

This paper cites BERTopic: Neural topic modeling with a class-based TF-IDF procedure.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation BERTopic: Neural topic modeling with a class-based TF-IDF procedure

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T10:43:18.402632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d48c13f-86fc-4071-889c-0f69045edd7f · outbound

This paper cites Is anyone responsible?: How television frames political issues.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Is anyone responsible?: How television frames political issues

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.624293Z

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 f47dbdf1-c70c-44ec-a8c7-450e05fc9dc2 · outbound

This paper cites Text classification algorithms: A survey.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Text classification algorithms: A survey

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.612136Z

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 84aa1691-4904-4dc3-9791-f75e32e4354a · outbound

This paper cites GDELT : Global data on events, location, and tone, 1979--2012.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation GDELT : Global data on events, location, and tone, 1979--2012

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.599440Z

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 689275eb-ff4e-418a-a144-3ec7566e1cae · outbound

This paper cites Text mining for social science--the state and the future of computational text analysis in sociology.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Text mining for social science--the state and the future of computational text analysis in sociology

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.585972Z

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 e40e7020-f102-4f97-89eb-1f2b45a7d51c · outbound

This paper cites an unresolved cited work.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:43:18.570792Z

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 6a97120b-a039-40f7-9f89-54227b6c228b · outbound

This paper cites GPT-4 technical report, 2023.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation GPT-4 technical report, 2023

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.557742Z

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 70ced5c4-76d7-4de6-8f06-7d8114e24b8e · outbound

This paper cites TopicGPT: A Prompt-based Topic Modeling Framework.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation TopicGPT: A Prompt-based Topic Modeling Framework

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T10:43:18.431324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 592323fd-9623-4d80-ad42-833c74e994b6 · outbound

This paper cites Tired of Topic Models? Clusters of Pretrained Word Embeddings Make for Fast and Good Topics too!.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Tired of Topic Models? Clusters of Pretrained Word Embeddings Make for Fast and Good Topics too!

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T10:43:18.435324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44424eb0-84c0-4562-97ec-eaa42cd84367 · outbound

This paper cites Schuck Sophie Lecheler, Mario Keer and Regula Hänggli.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Schuck Sophie Lecheler, Mario Keer and Regula Hänggli

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.544191Z

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 9abecca5-ae83-4e22-bd22-8db9ae874c51 · outbound

This paper cites How a conservative activist invented the conflict over critical race theory.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation How a conservative activist invented the conflict over critical race theory

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.531343Z

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 21d7bd70-a8b8-4c93-bb1e-607fceb21d1a · outbound

This paper cites Source-lda: Enhancing probabilistic topic models using prior knowledge sources.

Creating Targeted, Interpretable Topic Models with LLM-Generated Text Augmentation Source-lda: Enhancing probabilistic topic models using prior knowledge sources

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:43:18.518421Z

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.

Pith citing papers

No inbound Pith citation observations are available.