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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.

pith.paper-citation-record.v1
2309.17234 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:41:36.927901Z

measured 0 of 1 external citation measurements

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.

source=pdf_text observed=2026-08-07T10:41:36.927901Z digest=sha256:a1e8dc4c15aba12e114dd2d26664066194d2e5fd1fcff6873492339fded581e9

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.

source=pdf_text observed=2026-08-06T22:49:37.942223Z digest=sha256:8dc6479f3249b3c83e7f0f62c394995fccb774857105a579549a4895be6e9e8d

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.

source=pdf_text observed=2026-08-06T19:11:23.724411Z digest=sha256:09ac6d1e1c1eae36f03e331d06bf344340a56c135efa6705dcc186395b46ed0d

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.

source=pdf_text observed=2026-08-06T18:24:53.304098Z digest=sha256:9c56ce07ab304229df441b0b87c547c6e01500179ce8569381b3b893b85f319f

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.

source=pdf_text observed=2026-08-04T18:34:13.108989Z digest=sha256:21c367806eaf5a4c7f1ccbda538f46ca74184da5f16af09f05a745eff035cc48

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T11:28:30.771042Z digest=sha256:a8ac1339c0e8da17456ae12ce056fff1f1b7b6c7e51308306b175e159f167568

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-14T21:14:58.531470Z digest=sha256:a477575d6556a8d92bd35fb54622c6b17a806cd74a56258fb9e4e118e9fad5d8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T13:40:04.275438Z digest=sha256:5d26394133c466d35cb2450b2c4b3d91633fc0eb149b86f0e8cac18f08094385

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T19:58:32.016341Z digest=sha256:7a7a0a9cc9678dd24aab63c8e6b16c5d2d46556039203be3423e1e7ca5a026d4