Paper Citation Record · LEDGER

GameEval: Evaluating LLMs on Conversational Games

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2308.10032.

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

pith.paper-citation-record.v1
2308.10032 v1

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

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:50:32.960122Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T22:32:43.962947Z

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 436ad5c1-d7a0-493f-a7c4-04493e4a8b0a · inbound

Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers cites this paper.

Game Theory Meets Large Language Models: A Systematic Survey with Taxonomy and New Frontiers GameEval: Evaluating LLMs on Conversational Games

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T22:50:32.960122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef4dd5ca-d0f2-4830-a96b-26312327dea1 · inbound

lmgame-Bench: How Good are LLMs at Playing Games? cites this paper.

lmgame-Bench: How Good are LLMs at Playing Games? GameEval: Evaluating LLMs on Conversational Games

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:01.892670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbd1ebb1-33ab-4190-9d6e-d788077e060c · inbound

ARIA: Training Language Agents with Intention-Driven Reward Aggregation cites this paper.

ARIA: Training Language Agents with Intention-Driven Reward Aggregation GameEval: Evaluating LLMs on Conversational Games

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:09:02.360560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bf281a7-86d2-4a1c-ac14-7c08207e2fba · inbound

Common-agency Games for Multi-Objective Test-Time Alignment cites this paper.

Common-agency Games for Multi-Objective Test-Time Alignment GameEval: Evaluating LLMs on Conversational Games

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:15:06.699406Z

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.

Observation 25e3cbf4-d3f6-4ef6-9ecd-c4db154d670a · inbound

Multi-Turn Multi-Agent Dialogue for Collaborative Reconstruction Improves VLM Performance on Spatial Reasoning, But Only Barely cites this paper.

Multi-Turn Multi-Agent Dialogue for Collaborative Reconstruction Improves VLM Performance on Spatial Reasoning, But Only Barely GameEval: Evaluating LLMs on Conversational Games

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T22:32:43.964469Z

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.