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Paper Citation Record · LEDGER

Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2508.20697.

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

pith.paper-citation-record.v1
2508.20697 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T09:47:40.850633Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 56531e6d-07da-4ead-9e20-e68dd9cdbca4 · inbound

STEP-LLM: Generating CAD STEP Models from Natural Language with Large Language Models cites this paper.

STEP-LLM: Generating CAD STEP Models from Natural Language with Large Language Models Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-03T09:47:40.850633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:47:40.850633Z digest=sha256:5ea2bb9657cc72a64df820ad909609befe04a37f335f80703f881cd9e30595d9

Observation 19980134-ab0e-44b6-b484-fb663711537f · inbound

Delving into the Temporal Challenges of Unified Video Protection Against Image-to-Video and Fine-Tuning-based Customization cites this paper.

Delving into the Temporal Challenges of Unified Video Protection Against Image-to-Video and Fine-Tuning-based Customization Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-02T05:32:27.018224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:32:27.018224Z digest=sha256:e5f53c2996e14a4e529efe30e0c2cd01de8045d1f9cc15ceeb5bc2c5594e151a