Paper Citation Record · LEDGER

LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.16499.

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

pith.paper-citation-record.v1
2402.16499 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:48:33.212716Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:58:02.861814Z

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 d177b8cc-07a0-492d-b517-2a0dd8e09e10 · inbound

Research Community Perspectives on "Intelligence" and Large Language Models cites this paper.

Research Community Perspectives on "Intelligence" and Large Language Models LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:48:33.212716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a69fee3-6e9d-4659-b1ea-de91371f6dc3 · inbound

VS-Bench: Evaluating VLMs for Strategic Abilities in Multi-Agent Environments cites this paper.

VS-Bench: Evaluating VLMs for Strategic Abilities in Multi-Agent Environments LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-19T11:57:16.235263Z

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 00291ad2-99ed-4c44-819a-1ba896806145 · inbound

Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review cites this paper.

Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments

Reference 149

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:58.977327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f13d126-faea-4674-9bcd-035587ad398d · inbound

Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application cites this paper.

Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments

Reference 124

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:58:02.863942Z

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.