Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2309.17234.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:41:36.927901Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T20:57:23.844144Z
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 1f7aa7f0-6415-470d-8018-d8c7fe82ddb8 · inbound
Empowering Economic Simulation for Massively Multiplayer Online Games through Generative Agent-Based Modeling cites this paper.
Empowering Economic Simulation for Massively Multiplayer Online Games through Generative Agent-Based Modeling Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:41:36.927901Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eb22f23c-b67e-4da7-9faa-36e978f4d73e · inbound
The Decrypto Benchmark for Multi-Agent Reasoning and Theory of Mind cites this paper.
The Decrypto Benchmark for Multi-Agent Reasoning and Theory of Mind Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:49:37.942223Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cfab6950-fd94-42ce-9bf7-ac42c36c9807 · inbound
Too Human to Model:The Uncanny Valley of LLMs in Social Simulation -- When Generative Language Agents Misalign with Modelling Principles cites this paper.
Too Human to Model:The Uncanny Valley of LLMs in Social Simulation -- When Generative Language Agents Misalign with Modelling Principles Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:11:23.724411Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5fd0236e-dc05-4f9c-9bc9-f568063335bd · 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 Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:24:53.304098Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 893e5357-f9a3-455e-9ea8-dd0bd17c19b7 · inbound
Tackling One Health Risks: How Large Language Models are leveraged for Risk Negotiation and Consensus-building cites this paper.
Tackling One Health Risks: How Large Language Models are leveraged for Risk Negotiation and Consensus-building Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T18:34:13.108989Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c6905c6e-9193-4f62-a8f4-b3dabf64fb00 · inbound
A Benchmark for Multi-Party Negotiation Games from Real Negotiation Data cites this paper.
A Benchmark for Multi-Party Negotiation Games from Real Negotiation Data Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Reference 1
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-15T11:29:58.693674Z
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.
Observation 2b4a7c5e-cdff-4a27-95a7-eff6b6a77f4d · inbound
Talk is Cheap, Communication is Hard: Dynamic Grounding Failures and Repair in Multi-Agent Negotiation cites this paper.
Talk is Cheap, Communication is Hard: Dynamic Grounding Failures and Repair in Multi-Agent Negotiation Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T21:17:59.405435Z
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.
Observation 66be8884-aead-49a1-b60e-5711656e3c6c · inbound
Stop Drawing Scientific Claims from LLM Social Simulations Without Robustness Audits cites this paper.
Stop Drawing Scientific Claims from LLM Social Simulations Without Robustness Audits Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T13:43:19.649387Z
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.
Observation a5c25b66-d517-4fe8-a6bc-0131beaa89cc · inbound
DICE: Entropy-Regularized Equilibrium Selection for Stable Multi-Agent LLM Coordination cites this paper.
DICE: Entropy-Regularized Equilibrium Selection for Stable Multi-Agent LLM Coordination Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Reference 23
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T20:57:23.845785Z
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.