Paper Citation Record · LEDGER

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification

As of 9 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2506.04693.

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

pith.paper-citation-record.v1
2506.04693 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:41:46.129598Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

17 of 17 outbound references displayed

verified exact0
verified fuzzy8
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 27c11d75-09d3-4500-a889-b9295715c8fb · outbound

This paper cites In Chinese datasets, speakers often use the initial letters of Chinese pinyin for abbreviations.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification In Chinese datasets, speakers often use the initial letters of Chinese pinyin for abbreviations

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:46.320914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 231fd26b-7aa1-495e-b2eb-68dbb81789ed · outbound

This paper cites Speakers liken a certain group to animals or describe a group or object using animal behav- ior, or they may use specific things or events to describe a group or object.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification Speakers liken a certain group to animals or describe a group or object using animal behav- ior, or they may use specific things or events to describe a group or object

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:46.310908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 487726b1-7664-4eb8-a556-cc1e3cd2e8ab · outbound

This paper cites an unresolved cited work.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:41:46.301633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2cda885f-b876-4d56-a149-ed9f04cd997d · outbound

This paper cites Examples: •艾呀，梅关系，不会疣事的，概率为淋。疣其湿没有尖锐的问题就更不担心啦，你要照顾好滋己呀，不要经常去疱吧了，找个斑上吧，疹心的。 Oh dear, don’t worry, everything will be fine, the probability is zero.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification Examples: •艾呀，梅关系，不会疣事的，概率为淋。疣其湿没有尖锐的问题就更不担心啦，你要照顾好滋己呀，不要经常去疱吧了，找个斑上吧，疹心的。 Oh dear, don’t worry, everything will be fine, the probability is zero

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:46.292327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f1242c3a-633b-450c-9d69-bbf3f8add63f · outbound

This paper cites InTENCON 2022- 2022 IEEE Region 10 Conference (TENCON), pages 1–4.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification InTENCON 2022- 2022 IEEE Region 10 Conference (TENCON), pages 1–4

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:46.330092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d11f9b39-f322-4e43-9a51-12708a4ddc5c · outbound

This paper cites Harmful Suicide Content Detection.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification Harmful Suicide Content Detection

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T10:41:46.189209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 70e1f11f-5703-48d8-8750-5af9ba1fb3e2 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:46.095438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a331aef0-4d19-4abe-8d82-33d102492663 · outbound

This paper cites For example, The character ‘默’(silence) is composed of ‘ 黑’ (black) + ‘犬’ (dog), which is used to mock black peo- ple.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification For example, The character ‘默’(silence) is composed of ‘ 黑’ (black) + ‘犬’ (dog), which is used to mock black peo- ple

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:46.262463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 379c884f-de82-4949-9878-ed73553b0d13 · outbound

This paper cites an unresolved cited work.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:41:46.253184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5f77b10c-2718-4750-a23c-6a4092734c96 · outbound

This paper cites This answer may be explicit or implicit.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification This answer may be explicit or implicit

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:46.244016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bdc46f20-3eb8-4e6f-84f4-f6529d9d0146 · outbound

This paper cites For instance, 基佬(gay) originally appeared as a dialect in the Guangdong region.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification For instance, 基佬(gay) originally appeared as a dialect in the Guangdong region

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:46.282359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 293d46f8-8ef1-4d60-8857-1f7653e7f4a7 · outbound

This paper cites Generally, loanwords do not in- clude translated words but refer to words that are absorbed with both sound and meaning.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification Generally, loanwords do not in- clude translated words but refer to words that are absorbed with both sound and meaning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:41:46.272699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e9fa2b98-a073-4e00-9be1-4e5733701dcb · outbound

This paper cites ToxVis: Enabling Interpretability of Implicit vs. Explicit Toxicity Detection Models with Interactive Visualization.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification ToxVis: Enabling Interpretability of Implicit vs. Explicit Toxicity Detection Models with Interactive Visualization

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:46.079399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fc16026-ac01-4910-84fe-9b04f779dda5 · outbound

This paper cites Entendre, a Social Bot Detection Tool for Niche, Fringe, and Extreme Social Media.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification Entendre, a Social Bot Detection Tool for Niche, Fringe, and Extreme Social Media

Reference 2021

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T10:41:46.162540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4496ac46-75ae-4d43-a1da-6cd7ebcab1fb · outbound

This paper cites Twitter Users' Behavioral Response to Toxic Replies.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification Twitter Users' Behavioral Response to Toxic Replies

Reference 2022

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T10:41:46.233820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 36e5539a-bf9a-4b51-b6a6-1cee77c14e4c · outbound

This paper cites Rule By Example: Harnessing Logical Rules for Explainable Hate Speech Detection.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification Rule By Example: Harnessing Logical Rules for Explainable Hate Speech Detection

Reference 2023

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T10:41:46.220590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 40785042-7f9a-4868-a498-bcb0239bead5 · outbound

This paper cites ReZG: Retrieval-Augmented Zero-Shot Counter Narrative Generation for Hate Speech.

Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification ReZG: Retrieval-Augmented Zero-Shot Counter Narrative Generation for Hate Speech

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T10:41:46.083338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.