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Paper Citation Record · LEDGER

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech

As of 13 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2508.04638.

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

pith.paper-citation-record.v1
2508.04638 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:55:12.152499Z

measured 14 of 14 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-24T01:13:56.198861Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T01:15:54.366258Z

Reference resolution

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation af367d04-4e3d-4b28-85dd-84c5e88447b4 · outbound

This paper cites In Proceed- ings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5792–5809, Toronto, Canada.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech In Proceed- ings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5792–5809, Toronto, Canada

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:55:12.303306Z

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.

source=pdf_text observed=2026-08-05T23:55:12.125908Z digest=sha256:8fa9e598987d43e9032b97aaef0522408315eb937578f43ac1a888e231fbc083

Observation 68887c3e-2718-43e1-ab08-b464ca256313 · outbound

This paper cites CSEval: Towards Automated, Multi-Dimensional, and Reference-Free Counterspeech Evaluation using Auto-Calibrated LLMs.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech CSEval: Towards Automated, Multi-Dimensional, and Reference-Free Counterspeech Evaluation using Auto-Calibrated LLMs

Reference 6

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T23:55:12.234878Z

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.

source=pdf_text observed=2026-08-05T23:55:12.129138Z digest=sha256:bcfbdd160c98cb54c9861f3b9c6be2dc7c0ad0d991233c198f13bb724062bcfb

Observation 9300c002-c3a5-426c-b0e9-ff9304e26dc0 · outbound

This paper cites In Proceedings of the 2022 Conference on Empiri- cal Methods in Natural Language Processing, pages 10818–10833, Abu Dhabi, United Arab Emirates.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech In Proceedings of the 2022 Conference on Empiri- cal Methods in Natural Language Processing, pages 10818–10833, Abu Dhabi, United Arab Emirates

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:55:12.293542Z

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.

source=pdf_text observed=2026-08-05T23:55:12.132656Z digest=sha256:83baabd423c2195a6f2f66d8f18a2a73789a57d8870adc8f145ab9d917fd07c8

Observation 61e567ee-849c-4417-a9be-95c6a424f391 · outbound

This paper cites Korean Online Hate Speech Dataset for Multilabel Classification: How Can Social Science Improve Dataset on Hate Speech?.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech Korean Online Hate Speech Dataset for Multilabel Classification: How Can Social Science Improve Dataset on Hate Speech?

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T23:55:12.221266Z

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.

source=pdf_text observed=2026-08-05T23:55:12.136241Z digest=sha256:df575c9e282d53d41324439176eca00db727b08ef7d18f2918cecbab48f5df6f

Observation 10a3fda0-e143-4f12-a033-d814e84ac15c · outbound

This paper cites Analyzing the hate and counter speech accounts on Twitter.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech Analyzing the hate and counter speech accounts on Twitter

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T23:55:12.139508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:55:12.139508Z digest=sha256:266243121a1e40b786328043d937c77ab7d1020671d41d9654275a3ee2783858

Observation 0357108e-589c-4796-a2b7-affd37759038 · outbound

This paper cites Rescuing Counterspeech: A Bridging-Based Approach to Combating Misinformation.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech Rescuing Counterspeech: A Bridging-Based Approach to Combating Misinformation

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T23:55:12.142684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:55:12.142684Z digest=sha256:b880bd27bfe678ef72dbfe44d7af401609c4155161c2613fda17bd792e9af75e

Observation 356a0926-3e65-40f6-a0b3-828e8b8aabe2 · outbound

This paper cites Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:55:12.272814Z

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.

source=pdf_text observed=2026-08-05T23:55:12.152499Z digest=sha256:04f70a1107cd78f6ab81bb52936d501d001ba2ff3c40c9220f47947e71d692ec

Observation f1263eb3-a4d0-4f13-954b-b6345fe92e88 · outbound

This paper cites Marcus Tomalin and Stefanie Ullmann, editors.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech Marcus Tomalin and Stefanie Ullmann, editors

Reference 2017

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:55:12.283032Z

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.

source=pdf_text observed=2026-08-05T23:55:12.146016Z digest=sha256:3ccc293c9a79df4a1aa41365584de56cd830c13d6b8da2bcd20df151e2777dff

Observation 15ce4030-c739-42e6-9c8a-ea8b098d9946 · outbound

This paper cites CODEOFCONDUCT at Multilingual Counterspeech Generation: A Context-Aware Model for Robust Counterspeech Generation in Low-Resource Languages.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech CODEOFCONDUCT at Multilingual Counterspeech Generation: A Context-Aware Model for Robust Counterspeech Generation in Low-Resource Languages

Reference 2019

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T23:55:12.248487Z

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.

source=pdf_text observed=2026-08-05T23:55:12.115317Z digest=sha256:16bd0ebba66d95663e375e737b38fd2dcee627c986a8b8552eb4ab49a875e021

Observation c8273a02-9425-4fca-b53b-6e0e3545e19b · outbound

This paper cites In Pro- ceedings of the Fourth Workshop on Online Abuse and Harms, pages 102–112, Online.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech In Pro- ceedings of the Fourth Workshop on Online Abuse and Harms, pages 102–112, Online

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:55:12.312518Z

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.

source=pdf_text observed=2026-08-05T23:55:12.122651Z digest=sha256:ca89a7dab5520257da4686951f4605b92718a36ee3b5fbe5f57a42820961397d

Observation 5f2d1f9e-b082-497d-b2f9-693ce80242c6 · outbound

This paper cites Counter Hate Speech in Social Media: A Survey.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech Counter Hate Speech in Social Media: A Survey

Reference 2022

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T23:55:12.262236Z

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.

source=pdf_text observed=2026-08-05T23:55:12.111359Z digest=sha256:2ec2f45f7a3442a8c6cf7ade3b595fa805afd032485a83de5532f1697ba88914

Observation 151f267e-2e89-4436-8f17-5636bcb24e1a · outbound

This paper cites EPJ Data Science, 12:1.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech EPJ Data Science, 12:1

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:55:12.321769Z

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.

source=pdf_text observed=2026-08-05T23:55:12.119257Z digest=sha256:b8f2da8d4befe8db7b1ca4881ab0132d3a9856e7994ecfce5192c54123c56d51

Observation 9f52c7e5-8477-4cba-8984-c5570d50057d · outbound

This paper cites Northeastern Uni at Multilingual Counterspeech Generation: Enhancing Counter Speech Generation with LLM Alignment through Direct Preference Optimization.

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech Northeastern Uni at Multilingual Counterspeech Generation: Enhancing Counter Speech Generation with LLM Alignment through Direct Preference Optimization

Reference 2024

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T23:55:12.187414Z

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.

source=pdf_text observed=2026-08-05T23:55:12.149307Z digest=sha256:d5ed0f9c0afa7fd79fb60c61a770f1431ba815a60ab064aeb58668e96a4a7944

Pith citing papers

Observation fcf5ed53-ef34-4b77-ad77-f317a6ce92b0 · inbound

Assessing How Hate, Counterspeech, and Toxicity Affect Hate Group Newcomers cites this paper.

Assessing How Hate, Counterspeech, and Toxicity Affect Hate Group Newcomers Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-24T01:15:54.369960Z

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.

source=arxiv_source observed=2026-05-24T01:13:56.198861Z digest=sha256:a0f264c09d55ac865f16860360dc28d47d6e46bc6b810c16f9604e491e558611