Paper Citation Record · LEDGER

The Majority is not always right: RL training for solution aggregation

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2509.06870.

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

pith.paper-citation-record.v1
2509.06870 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T11:44:22.344517Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:40:08.281402Z

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 a6e26b5f-d64a-4902-a3dc-db33497432dc · inbound

Evolutionary Profiles for Protein Fitness Prediction cites this paper.

Evolutionary Profiles for Protein Fitness Prediction The Majority is not always right: RL training for solution aggregation

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-18T09:01:09.671919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 62e3d405-6efa-40e4-ab05-18fd40f6e5a3 · inbound

Demystifying Multi-Agent Debate: The Role of Confidence and Diversity cites this paper.

Demystifying Multi-Agent Debate: The Role of Confidence and Diversity The Majority is not always right: RL training for solution aggregation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T11:44:22.344517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1f4205f-c244-443a-9783-f5a56707a7bd · inbound

MoCo: A One-Stop Shop for Model Collaboration Research cites this paper.

MoCo: A One-Stop Shop for Model Collaboration Research The Majority is not always right: RL training for solution aggregation

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-16T10:17:43.763828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ddb9fb00-fec4-4199-aca8-14bcbad2a379 · inbound

Efficient Reasoning on the Edge cites this paper.

Efficient Reasoning on the Edge The Majority is not always right: RL training for solution aggregation

Reference 84

Resolution: unresolved; no resolver link, observed 2026-07-13T23:28:12.790404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb0f0e4e-ee17-45d2-b207-1a6183c422ba · inbound

Understanding Performance Gap Between Parallel and Sequential Sampling in Large Reasoning Models cites this paper.

Understanding Performance Gap Between Parallel and Sequential Sampling in Large Reasoning Models The Majority is not always right: RL training for solution aggregation

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:20:52.463558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8d1d1980-7186-4efb-96b2-00e724a171aa · inbound

LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling cites this paper.

LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling The Majority is not always right: RL training for solution aggregation

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:10:58.109816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 40c90944-5dd9-48cf-912b-3373a93a9598 · inbound

LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling cites this paper.

LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling The Majority is not always right: RL training for solution aggregation

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:12:28.331875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7732f651-d6c9-4533-94a3-a5e0a393515b · inbound

CAPS: Cascaded Adaptive Pairwise Selection for Efficient Parallel Reasoning cites this paper.

CAPS: Cascaded Adaptive Pairwise Selection for Efficient Parallel Reasoning The Majority is not always right: RL training for solution aggregation

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-19T15:42:38.386015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 48fca032-9f85-4661-bca5-d45c888c86e6 · inbound

AgentFugue: Agent Scaling for Long-Horizon Tasks through Collective Reasoning cites this paper.

AgentFugue: Agent Scaling for Long-Horizon Tasks through Collective Reasoning The Majority is not always right: RL training for solution aggregation

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-06-30T13:34:40.439558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 895aa897-db85-468f-8112-f3c2c45045e1 · inbound

FineVerify: Scaling Test-Time Compute with Fine-Grained Self-Verification for Agentic Search cites this paper.

FineVerify: Scaling Test-Time Compute with Fine-Grained Self-Verification for Agentic Search The Majority is not always right: RL training for solution aggregation

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T19:12:35.005229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 629e359f-7e5d-4ea1-9475-5c25d3f90d17 · inbound

Multi-Agent Computer Use cites this paper.

Multi-Agent Computer Use The Majority is not always right: RL training for solution aggregation

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:06:25.097303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4db2c2e3-fe49-4d3c-9b4c-c3679d3e74c8 · inbound

Scaling Participation in Modular AI Systems cites this paper.

Scaling Participation in Modular AI Systems The Majority is not always right: RL training for solution aggregation

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T18:57:16.583268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation e8c9da9b-852a-4bd0-a110-ea27ddf38415 · inbound

Autodata: An agentic data scientist to create high quality synthetic data cites this paper.

Autodata: An agentic data scientist to create high quality synthetic data The Majority is not always right: RL training for solution aggregation

Reference 124

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:40:08.283233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 3b2edf05-29c8-49d0-991c-ff18678d75e3 · inbound

Autodata: An agentic data scientist to create high quality synthetic data cites this paper.

Autodata: An agentic data scientist to create high quality synthetic data The Majority is not always right: RL training for solution aggregation

Reference 124

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:19:51.228081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation cd10e78d-3eb5-4460-8ce0-13b9e574f31e · inbound

Autodata: An agentic data scientist to create high quality synthetic data cites this paper.

Autodata: An agentic data scientist to create high quality synthetic data The Majority is not always right: RL training for solution aggregation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-12T12:08:06.206832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.