Pith. sign in

Paper Citation Record · LEDGER

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

As of 10 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 2026-08-10T06:31:04.303077+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=sha256:7fd7f5b31fa9345e8860d0228a813639bdec00025092c5dd6f7edd12ea5d4f4e

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=sha256:2b7943e88fe21a4086b8c4a30a8127d11b9eefe7e9ddbcf57f733640dd39e71a

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:fb236423270f16b0cbc9c1ab8883595fea04fbb62fc4152ac0df7117d89a188b

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=sha256:70a37dafbc695d769c895a6aea15dc2a011e951d8055ccee5161b14b9de8b094

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:ef00c0515aa92bc1d2432f23ba852df19b1637e66049db1fce81680b7a040150

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T12:09:32.204944Z digest=sha256:90cba497935ee79c5acd45570b3185002294aa46ffc986b7f0c0fc86a3200b38

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T07:05:10.560865Z digest=sha256:0073119426d239518c21588706b5a7fe5184ccbd11137d60814f6e0bdb27901d

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:ebd405e4e0c2b21ab43ecd6633544a7862d180c36013d2b17148e7b055cd26f0