Pith. sign in

Paper Citation Record · LEDGER

Conditioning Large Language Models on Legal Systems? Detecting Punishable Hate Speech

As of 10 August 2026, this Paper Citation Record lists 3 of 3 outbound references and 0 inbound Pith citation observations for arXiv:2506.03009.

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

pith.paper-citation-record.v1
2506.03009 v1

Coverage vector

measured 3 of 3 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:15:42.661254Z

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

3 of 3 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 617f2baa-3519-4ab3-8d0b-2a350fd2ca9f · outbound

This paper cites an unresolved cited work.

Conditioning Large Language Models on Legal Systems? Detecting Punishable Hate Speech Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:15:42.989811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T11:15:42.580040Z digest=sha256:ce8ccf2ba12b7b9e6d871fdea0b82eb949d42f6661cafc6afae55de6c39fb976

Observation f1ffbe7a-20cc-4f4f-9204-ce485b83cf64 · outbound

This paper cites C Examplary Prompts In this section, we provide example prompts for the dierent approaches, corresponding to the dierent levels of abstractions of the legal system.

Conditioning Large Language Models on Legal Systems? Detecting Punishable Hate Speech C Examplary Prompts In this section, we provide example prompts for the dierent approaches, corresponding to the dierent levels of abstractions of the legal system

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:15:42.844377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T11:15:42.661254Z digest=sha256:2d816fe51bcee4c9dd04bc55bbc474951d62ead8badca16b151d912adde55195

Observation 86d5a95f-ec2c-4e81-a6c0-468bf3994132 · outbound

This paper cites Detecting Hate Speech with GPT-3.

Conditioning Large Language Models on Legal Systems? Detecting Punishable Hate Speech Detecting Hate Speech with GPT-3

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-07T11:15:42.505037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:15:42.505037Z digest=sha256:b329015d882e63bb4fd8098adbe7d0454da4fc8d4eadaf2b537f563c9efb0965

Pith citing papers

No inbound Pith citation observations are available.