Paper Citation Record · LEDGER

Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2412.06748.

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

pith.paper-citation-record.v1
2412.06748 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:27:34.924646Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T23:31:54.505691Z

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 c01ad35f-d372-4f9f-b395-75534335cdf1 · inbound

Linearly Decoding Refused Knowledge in Aligned Language Models cites this paper.

Linearly Decoding Refused Knowledge in Aligned Language Models Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T21:27:34.924646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7fea9ee-863f-40a8-a950-93d49e6e37b4 · inbound

ORFuzz: Fuzzing the "Other Side" of LLM Safety -- Testing Over-Refusal cites this paper.

ORFuzz: Fuzzing the "Other Side" of LLM Safety -- Testing Over-Refusal Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-18T23:31:54.511134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a161f0dc-f6f2-4fcf-8c5e-44d44cfe8f82 · inbound

Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection cites this paper.

Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T14:57:12.836202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6415b973-faae-41ad-87e8-f5a3dc7d50e5 · inbound

BAS: A Decision-Theoretic Approach to Evaluating Large Language Model Confidence cites this paper.

BAS: A Decision-Theoretic Approach to Evaluating Large Language Model Confidence Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-13T19:53:11.931957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.