Paper Citation Record · LEDGER

Leveraging Large Language Models and Topic Modeling for Toxicity Classification

As of 13 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2411.17876.

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

pith.paper-citation-record.v1
2411.17876 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:46:37.275386Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

25 of 25 outbound references displayed

verified exact0
verified fuzzy23
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0f9501ff-f500-4694-9c3b-8d66f6177cf8 · outbound

This paper cites Toxicity in chatgpt: Analyzing persona-assigned language models,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Toxicity in chatgpt: Analyzing persona-assigned language models,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.772310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f232e52b-ba36-48f5-aedc-43de2d91f851 · outbound

This paper cites ChatGPT,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification ChatGPT,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.747054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 53a1c804-938e-4da1-a4fc-8245879a1dbb · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.719558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2be23bf7-3295-4efa-9668-19b0ddfc0b65 · outbound

This paper cites Language models are unsupervised multitask learners,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Language models are unsupervised multitask learners,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T11:46:37.139748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d7f63c7-3edb-4b01-8081-20a4453b1fb0 · outbound

This paper cites mT5: A massively multilingual pre-trained text-to-text transformer,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification mT5: A massively multilingual pre-trained text-to-text transformer,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.687762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9b0990b2-7430-44f2-8796-569eebb39d94 · outbound

This paper cites Language models are few-shot learners,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Language models are few-shot learners,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.672095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 19d36f66-a5cb-4d46-b322-d032abbb8e82 · outbound

This paper cites A survey on large language models for code generation,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification A survey on large language models for code generation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.656215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b44934fe-b93f-4078-91e1-96cea53ceabe · outbound

This paper cites Sentiment analysis in the era of large language models: A reality check,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Sentiment analysis in the era of large language models: A reality check,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.638650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7166bdd0-38b8-4c97-aabb-f6fee44d894e · outbound

This paper cites Communication-Efficient and Tensorized Federated Fine-Tuning of Large Language Models.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Communication-Efficient and Tensorized Federated Fine-Tuning of Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T11:46:37.171631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac011411-9e43-487c-9cad-eb5aa3bef809 · outbound

This paper cites Efficient toxic content detection by bootstrapping and distilling large language models,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Efficient toxic content detection by bootstrapping and distilling large language models,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.621885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 952038fe-b053-41ac-b77f-442a75bbdaa7 · outbound

This paper cites “hot” chatgpt: The promise of chatgpt in detecting and discriminating hateful, offensive, and toxic comments on social media,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification “hot” chatgpt: The promise of chatgpt in detecting and discriminating hateful, offensive, and toxic comments on social media,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.604628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6a4fd072-a57e-46f0-90a2-369873e96b48 · outbound

This paper cites Exploring chatgpt for toxicity detection in github,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Exploring chatgpt for toxicity detection in github,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.585294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a3e495c3-5dd7-4474-9ea5-d0f6657294c3 · outbound

This paper cites COVID-19-related Nepali tweets clas- sification in a low resource setting,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification COVID-19-related Nepali tweets clas- sification in a low resource setting,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.568337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ca360040-2749-4d78-999b-754a1cffa458 · outbound

This paper cites Enhancing crisis-related tweet classification with entity-masked language modeling and multi- task learning,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Enhancing crisis-related tweet classification with entity-masked language modeling and multi- task learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.550974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 47ae560f-736a-4735-b690-250ca084e6d5 · outbound

This paper cites Topic modeling and sentiment analysis of global climate change tweets,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Topic modeling and sentiment analysis of global climate change tweets,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.533550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3a3607ac-bbf1-4548-aad2-ac185375c51f · outbound

This paper cites Not all comments are equal: Insights into comment moderation from a topic- aware model,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Not all comments are equal: Insights into comment moderation from a topic- aware model,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.516284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f6dd1b39-7a13-434b-a05b-728778b44f9e · outbound

This paper cites Topic enhanced word embedding for toxic content detection in q&a sites,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Topic enhanced word embedding for toxic content detection in q&a sites,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.497463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 22e7368b-8c52-4f18-b66f-6af61ab8af53 · outbound

This paper cites Latent dirichlet allocation,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Latent dirichlet allocation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.474532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 352ba91d-7388-4e4c-9e85-50ea1bc45a11 · outbound

This paper cites BERTweet: A pre-trained language model for English Tweets,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification BERTweet: A pre-trained language model for English Tweets,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.444681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fea1c1f0-9a9b-4095-a17e-45a00bdb7f99 · outbound

This paper cites HateBERT: Retraining BERT for abusive language detection in English,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification HateBERT: Retraining BERT for abusive language detection in English,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.425241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e5c7fdcb-6e5c-4e49-937c-44b849d1bbde · outbound

This paper cites NLPositionality: Characterizing design biases of datasets and models,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification NLPositionality: Characterizing design biases of datasets and models,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.794953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 13bc329d-b4c8-4144-adf6-32b44ce989b8 · outbound

This paper cites Toxigen: A large-scale machine- generated dataset for implicit and adversarial hate speech detection,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Toxigen: A large-scale machine- generated dataset for implicit and adversarial hate speech detection,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.407606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e1c52e54-58b4-4691-9815-6debbcf08c21 · outbound

This paper cites A concise review of transfer learning,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification A concise review of transfer learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.390856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e3be26dd-9838-4bde-9c1f-f8667de29ad1 · outbound

This paper cites Perspective api,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Perspective api,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.366740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4942a50a-6213-44c2-a159-1c8b09bfea83 · outbound

This paper cites Rewire api,.

Leveraging Large Language Models and Topic Modeling for Toxicity Classification Rewire api,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:46:37.347777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.