Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate System
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2312.04854.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T21:33:37.648798Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T06:16:28.064256Z
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 cdd5ec2c-03c3-41b1-afb4-994251091ef6 · inbound
S$^2$-MAD: Breaking the Token Barrier to Enhance Multi-Agent Debate Efficiency cites this paper.
S$^2$-MAD: Breaking the Token Barrier to Enhance Multi-Agent Debate Efficiency Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate System
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T21:33:37.648798Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6bdfe1e3-1c75-476f-ac35-8cbd9c1d404b · inbound
DSMentor: Enhancing Data Science Agents with Curriculum Learning and Online Knowledge Accumulation cites this paper.
DSMentor: Enhancing Data Science Agents with Curriculum Learning and Online Knowledge Accumulation Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate System
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:43:39.556316Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7fdca9d2-b637-4124-8643-a39c364f80e1 · inbound
Cross-Task Experiential Learning on LLM-based Multi-Agent Collaboration cites this paper.
Cross-Task Experiential Learning on LLM-based Multi-Agent Collaboration Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate System
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:59:57.249294Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ecbf8164-f67d-4952-ae71-e39811b224b1 · inbound
Finding Common Ground: Using Large Language Models to Detect Agreement in Multi-Agent Decision Conferences cites this paper.
Finding Common Ground: Using Large Language Models to Detect Agreement in Multi-Agent Decision Conferences Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate System
Reference 18
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T18:24:56.042027Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 9279f953-5a12-4a12-a9a6-b7628a93a43c · inbound
Interaction Protocol Shapes Moral Judgment in Multi-Agent Debate cites this paper.
Interaction Protocol Shapes Moral Judgment in Multi-Agent Debate Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate System
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T10:25:54.856989Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.