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Paper Citation Record · LEDGER

Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2404.10160.

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

pith.paper-citation-record.v1
2404.10160 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:21:26.267573Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T07:13:17.111251Z

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 6c9c34e7-12b4-48b7-ad9b-1ea84fb7f82d · inbound

BiasFilter: An Inference-Time Debiasing Framework for Large Language Models cites this paper.

BiasFilter: An Inference-Time Debiasing Framework for Large Language Models Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T13:21:26.267573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:21:26.267573Z digest=sha256:7a065c27e3e3fe753c5e912aa41439a03a1fa9fe72f88344e8ca7aed68fb54a0

Observation a9b58e95-7f39-4340-a98f-db94ec982535 · inbound

A Reward-driven Automated Webshell Malicious-code Generator for Red-teaming cites this paper.

A Reward-driven Automated Webshell Malicious-code Generator for Red-teaming Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T12:34:15.991645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:34:15.991645Z digest=sha256:2230fbb548e4a946a72a20ed2749e19a394ff13e265c5242d942a5ac1b702d14

Observation 9f94bc02-7923-4382-b861-49072d68835a · inbound

Detection, Classification, and Mitigation of Gender Bias in Large Language Models cites this paper.

Detection, Classification, and Mitigation of Gender Bias in Large Language Models Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T00:51:07.451148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:51:07.451148Z digest=sha256:4b840a8f1faf452af7d00d0a1cd1523f87c74b7b686788ca4fc4454b30dd6ac1

Observation 3f88de91-2b3b-4940-80db-e6b63800afc1 · inbound

MPF: Aligning and Debiasing Language Models post Deployment via Multi Perspective Fusion cites this paper.

MPF: Aligning and Debiasing Language Models post Deployment via Multi Perspective Fusion Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T20:33:26.058136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:33:26.058136Z digest=sha256:ab1a51e75e168354a34bd52ead54f5624e5cab12f2ac42ba7e4c837a19a70667

Observation 11e78ca6-e081-4f1e-a3fe-96054ea6fbaf · inbound

Mitigation of Gender and Ethnicity Bias in AI-Generated Stories through Model Explanations cites this paper.

Mitigation of Gender and Ethnicity Bias in AI-Generated Stories through Model Explanations Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

Reference 2009

Resolution
unresolved
no resolver link, observed 2026-08-05T11:22:28.908722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:22:28.908722Z digest=sha256:b0d17035c28667a2acf4235a04963ce6c0646adde6eea45ebce72c8da6753588

Observation 36025311-b4c9-42ef-8dea-3584f6186ecf · inbound

Membership Inference for Contrastive Pre-training Models with Text-only PII Queries cites this paper.

Membership Inference for Contrastive Pre-training Models with Text-only PII Queries Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-15T12:09:59.572627Z

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.

source=pdf_text observed=2026-05-15T12:09:32.204944Z digest=sha256:1a773b757d247922d6dab02eec1412f215aa72b914087c499d6e5e0516d23ecb

Observation e1085d0b-3705-4f31-81c8-c6b757d7c619 · inbound

HunterAgent: Neuro-Symbolic Attack Trace Reconstruction under Anti-Forensics cites this paper.

HunterAgent: Neuro-Symbolic Attack Trace Reconstruction under Anti-Forensics Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-06-29T07:13:17.113732Z

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.

source=pdf_text observed=2026-06-29T07:05:10.560865Z digest=sha256:a33aa8f33647d3d3a4e56e0c0f2a6046f5a5b8a73845340921e4acfcc08060b7

Observation e6a2a217-08f6-4426-a805-b98378701d00 · inbound

Multi-Agent Debate Strategies: Survey, Taxonomy, and Challenges cites this paper.

Multi-Agent Debate Strategies: Survey, Taxonomy, and Challenges Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-01T00:32:23.259316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:32:23.259316Z digest=sha256:4ee377d6c07a3af977c1a52ffb190de2130d58d0fd1b2cfa81494bd36d5a2720