Paper Citation Record · LEDGER

Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2412.18693.

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

pith.paper-citation-record.v1
2412.18693 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:02:47.195821Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T20:54:21.584820Z

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 2b1b7a8a-c76d-4627-961e-6017443a229b · inbound

Jailbreaking to Jailbreak cites this paper.

Jailbreaking to Jailbreak Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T17:02:47.195821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a57cad7f-0a66-442d-ba67-07d698debdec · inbound

Jailbreak-R1: Exploring the Jailbreak Capabilities of LLMs via Reinforcement Learning cites this paper.

Jailbreak-R1: Exploring the Jailbreak Capabilities of LLMs via Reinforcement Learning Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T12:01:08.215841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac7ef433-3e74-412b-8fe7-9589df932fb0 · inbound

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models cites this paper.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:47:06.264820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 536888bb-9079-4d5f-ab57-719aa7f2a0f4 · inbound

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities cites this paper.

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-19T05:52:07.721429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f65c26c6-c0b8-4993-b6c5-7d009c0c4e55 · inbound

From Seed to Harvest: Augmenting Human Creativity with AI for Red-teaming Text-to-Image Models cites this paper.

From Seed to Harvest: Augmenting Human Creativity with AI for Red-teaming Text-to-Image Models Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T14:45:20.401969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4861d50b-d0bd-417c-95cb-0513527f72a6 · inbound

Red-Bandit: Test-Time Adaptation for LLM Red-Teaming via Bandit-Guided LoRA Experts cites this paper.

Red-Bandit: Test-Time Adaptation for LLM Red-Teaming via Bandit-Guided LoRA Experts Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:54:21.586690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e8a800fe-adaf-4bc1-b6ff-5bf651c93279 · inbound

GPT-Red: Automated Red Teaming via Self-Play at Scale cites this paper.

GPT-Red: Automated Red Teaming via Self-Play at Scale Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-01T01:12:44.118461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.