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Paper Citation Record · LEDGER

CompeteAI: Understanding the Competition Dynamics in Large Language Model-based Agents

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.17512.

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

pith.paper-citation-record.v1
2310.17512 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T11:43:51.009800Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T12:26:31.497738Z

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 4ce6f650-8a93-4171-9bbd-8137397a106b · inbound

BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks cites this paper.

BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks CompeteAI: Understanding the Competition Dynamics in Large Language Model-based Agents

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T23:41:54.550461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-18T23:38:10.078340Z digest=sha256:7dfa255d5a1dd5c5824870b785cc4a5a53d5853bb7a5e82daf207a54758a3ea5

Observation 31e8e7c9-550b-467a-b458-1ec863cb63c5 · inbound

Token-Level LLM Collaboration via FusionRoute cites this paper.

Token-Level LLM Collaboration via FusionRoute CompeteAI: Understanding the Competition Dynamics in Large Language Model-based Agents

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-22T12:26:31.501851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T12:25:59.747665Z digest=sha256:563ee1c4c2708d9b6f78c8604c15d642815bcd10b32c41095bad3879a559d011

Observation bd7aed3d-0d4b-4b83-8f99-8e04c4ff332e · inbound

EconAI: Dynamic Persona Evolution and Memory-Aware Agents in Evolving Economic Environments cites this paper.

EconAI: Dynamic Persona Evolution and Memory-Aware Agents in Evolving Economic Environments CompeteAI: Understanding the Competition Dynamics in Large Language Model-based Agents

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T17:47:32.379888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-14T17:44:19.274990Z digest=sha256:472684e601fc6eb60b508e1b14e22a56d7fb48f758affd6963976eded85d5bf6

Observation f69a05c3-2062-4b10-96b2-fa820f0a9726 · inbound

AgentSociety 2: An Integrated Research Environment for Executable Social Science cites this paper.

AgentSociety 2: An Integrated Research Environment for Executable Social Science CompeteAI: Understanding the Competition Dynamics in Large Language Model-based Agents

Reference 111

Resolution
unresolved
no resolver link, observed 2026-08-02T11:43:51.009800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:43:51.009800Z digest=sha256:fe588150e1fbac3868b3a08ccbe41cf33423d1043a7b9c2e2e1c7d14e07bb3e7

Observation fdceb880-b61f-4f48-9ff8-cacc79e7e76e · inbound

Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex cites this paper.

Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex CompeteAI: Understanding the Competition Dynamics in Large Language Model-based Agents

Reference 197

Resolution
unresolved
no resolver link, observed 2026-07-31T23:52:06.598677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:52:06.598677Z digest=sha256:1170a1f76874c2316a49806b29c66f8012a1bf30cc8605829f7efd1a506b2ad3