Paper Citation Record · LEDGER

TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents

As of 8 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 4 inbound Pith citation observations for arXiv:2601.05899.

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

pith.paper-citation-record.v1
2601.05899 v2

Coverage vector

measured 8 of 8 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T11:34:15.008621Z

measured 12 of 12 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T21:55:17.509478Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T00:39:17.250711Z

Reference resolution

8 of 8 outbound references displayed

verified exact0
verified fuzzy0
unresolved7
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8f6f6950-e7e3-415d-ab1b-4dc4a342eda8 · outbound

This paper cites LLM-PySC2: Starcraft II learning environment for Large Language Models.

TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents LLM-PySC2: Starcraft II learning environment for Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T11:34:14.990826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d52522e1-52ef-42df-9819-876a01105c92 · outbound

This paper cites Instruction Tuning with GPT-4.

TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents Instruction Tuning with GPT-4

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T11:34:14.999477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70bd269b-f062-4edf-893c-b68dcac6c7d5 · outbound

This paper cites InInternational Multi- Conference on Artificial Intelligence Technology, 135–146.

TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents InInternational Multi- Conference on Artificial Intelligence Technology, 135–146

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-03T11:34:15.004871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97f471f9-1bc0-4763-a86e-55caebe366d5 · outbound

This paper cites StarCraft II: A New Challenge for Reinforcement Learning.

TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents StarCraft II: A New Challenge for Reinforcement Learning

Reference 2017

Resolution: malformed identifier; no resolver link, observed 2026-08-03T11:34:15.008621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09bbe44e-4f68-4fb4-bd3c-98ac0a86062b · outbound

This paper cites Unity: A General Platform for Intelligent Agents.

TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents Unity: A General Platform for Intelligent Agents

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-03T11:34:14.986806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5222ddac-9008-4acf-bcff-2fc69fa4c878 · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents AgentBench: Evaluating LLMs as Agents

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-03T11:34:14.995038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ffc34d0-535b-4821-b867-5c255564c7fc · outbound

This paper cites Exploring the intersection of Generative AI and Software Development.

TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents Exploring the intersection of Generative AI and Software Development

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T11:34:14.977472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd57e4d7-7060-479a-8847-77e65f44b828 · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T11:34:14.982572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 5c5eaf16-2180-4fe0-a4f5-44a045f7921f · inbound

Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse cites this paper.

Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents

Reference 173

Resolution: verified exact; arxiv_id, observed 2026-05-27T03:06:04.774353Z

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 95fcea6e-3297-4d41-bdf3-c464ae063ee2 · inbound

Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse cites this paper.

Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents

Reference 173

Resolution: verified exact; arxiv_id, observed 2026-05-27T03:06:04.774353Z

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 cf1c4d91-da6b-4afb-a2bd-275e7c4f1677 · inbound

RTSGameBench: An RTS Benchmark for Strategic Reasoning by Vision-Language Models cites this paper.

RTSGameBench: An RTS Benchmark for Strategic Reasoning by Vision-Language Models TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents

Reference 52

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T00:39:17.253166Z

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 402c0434-bb86-450c-abd7-4ab2ffa046ca · inbound

MARS-RA: Rank Aggregation for Credit Assignment via Multimodal Comparisons in Embodied Multi-Agent Cooperation cites this paper.

MARS-RA: Rank Aggregation for Credit Assignment via Multimodal Comparisons in Embodied Multi-Agent Cooperation TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents

Reference 116

Resolution: unresolved; no resolver link, observed 2026-07-31T21:55:17.509478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.