Paper Citation Record · LEDGER

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat

As of 14 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2607.29577.

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

pith.paper-citation-record.v1
2607.29577 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T04:15:06.330124Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

verified exact0
verified fuzzy0
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation db8355d4-070f-43c9-bf89-5ad59f728689 · outbound

This paper cites OpenSpiel: A Framework for Reinforcement Learning in Games.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat OpenSpiel: A Framework for Reinforcement Learning in Games

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:05.822497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 445e54d1-df97-4dd7-9041-7ee7213ad898 · outbound

This paper cites Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:05.886907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3cfa10d-5cd9-48a2-8036-69dc7653fd14 · outbound

This paper cites BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:06.000334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7bac09c-82ec-40ea-aff7-408267d2403b · outbound

This paper cites The StarCraft Multi-Agent Challenge.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat The StarCraft Multi-Agent Challenge

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:06.067394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa1993d8-c6eb-4706-9ca9-77f389addc25 · outbound

This paper cites SmartPlay: A Benchmark for LLMs as Intelligent Agents.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat SmartPlay: A Benchmark for LLMs as Intelligent Agents

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:06.235494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d3a51d0-1f30-4ad5-a83f-f6ab905d3787 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat ReAct: Synergizing Reasoning and Acting in Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:06.330124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c762bc2e-bd9d-408f-a772-383437155fa3 · outbound

This paper cites Benchmarking the Spectrum of Agent Capabilities.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat Benchmarking the Spectrum of Agent Capabilities

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:05.687146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ac0af2d-135f-4ac6-bca6-709b74873b7b · outbound

This paper cites Reinforcement Learning Environment with LLM-Controlled Adversary in D&D 5th Edition Combat.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat Reinforcement Learning Environment with LLM-Controlled Adversary in D&D 5th Edition Combat

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:05.479917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7b880de-8f24-4a9e-880a-da7327bf6255 · outbound

This paper cites Factorio Learning Environment.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat Factorio Learning Environment

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:05.755199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcb1dcb2-117f-4beb-b8f9-8949176a7b53 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:06.169450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ae13bb3-adea-4397-ba12-77213ceebecb · outbound

This paper cites OpenAI Gym.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat OpenAI Gym

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:05.382746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bcbad1a-ce27-4c67-9e50-ac4cf8d5ab1f · outbound

This paper cites SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning.

DungeonBench: A Benchmark for Rules-Rich Tactical Reasoning in Dungeons & Dragons Combat SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:05.572715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.