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Paper Citation Record · LEDGER

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models

As of 12 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2507.12666.

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

pith.paper-citation-record.v1
2507.12666 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:47:25.181509Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

26 of 26 outbound references displayed

  • verified exact1
  • verified fuzzy18
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8be4dd52-b55f-4d19-8b79-a125121762d3 · outbound

This paper cites Deep reinforcement learning at the edge of the statistical precipice.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Deep reinforcement learning at the edge of the statistical precipice

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:28.582241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:22.820069Z digest=sha256:0c3010d1a025ea3d9d4705ad9568c598f13b1da8965099c81de1423317ed7ab4

Observation cab5262a-dbf4-45ff-bd75-af2aeed211bd · outbound

This paper cites The I nk S plotch E ffect: A case study on ChatGPT as a co-creative game designer.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models The I nk S plotch E ffect: A case study on ChatGPT as a co-creative game designer

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:28.440178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:22.909174Z digest=sha256:7b9a772e263a230637ac894d8ab7802eac04da924f5773c32452f7f95b321bce

Observation efe3c378-84c2-4596-93b7-8dd60da6e8f3 · outbound

This paper cites Dota 2 with Large Scale Deep Reinforcement Learning.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Dota 2 with Large Scale Deep Reinforcement Learning

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T16:47:23.007820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:47:23.007820Z digest=sha256:b92db745dfb0ceebe083180d844c30e86b22500344f74c171e4d30a68aab31a0

Observation b2e3eb37-cd9d-4fe5-9610-328f71a18576 · outbound

This paper cites Playing F lappy B ird based on motion recognition using a transformer model and LIDAR sensor.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Playing F lappy B ird based on motion recognition using a transformer model and LIDAR sensor

Reference 4

Resolution
verified exact
doi, observed 2026-08-06T16:47:25.418686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:23.107024Z digest=sha256:b0d7d95d93c1a156958527dbb3c962c371b80ef7c337b75f36f7db6142dc38f5

Observation 8e469dfb-37f8-49a1-a6a5-dc0a2be3dae6 · outbound

This paper cites Adversarial reinforcement learning for procedural content generation.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Adversarial reinforcement learning for procedural content generation

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:28.310086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:23.240291Z digest=sha256:92e67612208cc25be39d27c397b93f3024274568df37f380b583ebfabe2e5a8e

Observation b1b3a1ad-4929-4d36-a34f-fa75294232ae · outbound

This paper cites Mastering diverse control tasks through world models.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Mastering diverse control tasks through world models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T16:47:23.346837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:47:23.346837Z digest=sha256:b970912842c8d02905c5ca5479cfbbd00e915eb2b0f54aea8355ff6b026d9f83

Observation 76761cd2-2112-4b5c-91af-41e6d8f7e70d · outbound

This paper cites Gen2Sim : Scaling up robot learning in simulation with generative models.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Gen2Sim : Scaling up robot learning in simulation with generative models

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:28.160197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:23.443980Z digest=sha256:6786edb8696c960d74408d0e7bf7df203c4cf185f12a2189b2f2f57c8702bf80

Observation 0b538b68-29d6-4ed4-9463-73b8149d6791 · outbound

This paper cites PCGRL : Procedural content generation via reinforcement learning.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models PCGRL : Procedural content generation via reinforcement learning

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:28.041064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:23.538564Z digest=sha256:67f6eabf8f3194296b2f44c9e2cb14bdd6e5441b671899f05eda939da0d08cec

Observation ab8eae8f-3740-4a5a-9df8-743371bebefb · outbound

This paper cites Reward design with language models.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Reward design with language models

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:27.918136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:23.637237Z digest=sha256:6b9cfef721186143a90d6eff06e9dcc98a722ddfc67e086cfc4c6edf300d3949

Observation 87fc441e-0cfc-4dbe-84b1-1d9eceffec97 · outbound

This paper cites Eureka: Human-level reward design via coding large language models.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Eureka: Human-level reward design via coding large language models

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:27.718318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:23.735178Z digest=sha256:c8f754378eb82bb2c3a937d312ecbe6f39bb36404fee45589286f54fe15cf591

Observation e931b437-312a-49a0-9996-6778873a959c · outbound

This paper cites DrEureka : Language model guided sim-to-real transfer.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models DrEureka : Language model guided sim-to-real transfer

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:27.524926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:23.834414Z digest=sha256:bf8ef10bc6bbbda690b924a2b0fa138be4451b01560fff5b3164d97c2f39de2e

Observation f54fb9ee-77ac-4692-afdd-f848d8155407 · outbound

This paper cites Human-level control through deep reinforcement learning.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Human-level control through deep reinforcement learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T16:47:23.934263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:47:23.934263Z digest=sha256:813b354a27004a7b2c22da13961e97469ffdae66e6c6ecd8c39a47dd3da3733e

Observation 140537b6-f9e5-4b9d-a733-4f35bd750442 · outbound

This paper cites MAESTRO : Open-ended environment design for multi-agent reinforcement learning.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models MAESTRO : Open-ended environment design for multi-agent reinforcement learning

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:27.339163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:24.032973Z digest=sha256:22e03d2970f3908124736260cd601c985ceae503f2a2ab493f53c6ab6bb87f56

Observation 4a9086fd-42b0-45d5-8527-60c0e5f65ee6 · outbound

This paper cites A general reinforcement learning algorithm that masters chess, shogi, and go through self-play.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models A general reinforcement learning algorithm that masters chess, shogi, and go through self-play

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T16:47:24.152678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:47:24.152678Z digest=sha256:6d007f39a43e540c30c24cb4b45338d16bf4794af90c9a3e4a01a8059ee8c893

Observation 23c62845-b9db-4975-b2ea-c7aabaade011 · outbound

This paper cites Open-Ended Learning Leads to Generally Capable Agents.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Open-Ended Learning Leads to Generally Capable Agents

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T16:47:24.273683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:47:24.273683Z digest=sha256:55496a58531bbc3ba70c786dfdda8bfa66621dc261057b0eb5dfa7ab498304e8

Observation b5d9b907-689d-444a-bac6-9813077061e7 · outbound

This paper cites MarioGPT : Open-ended text2level generation through large language models.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models MarioGPT : Open-ended text2level generation through large language models

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:27.109329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:24.367020Z digest=sha256:6abee0472fbc7d7b612a20ce0091fbcf7ad5989c3ee430312528482dbc1d27c7

Observation ce2a29f9-8b65-4488-ba2e-23cfee6802ac · outbound

This paper cites FactorSim : Generative simulation via factorized representation.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models FactorSim : Generative simulation via factorized representation

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:26.957193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:24.452986Z digest=sha256:260880d604f63f49e457739893b8332aa06345dea960ac70e91cc663d3b89001

Observation c958d56f-acf5-4444-bbd0-3fb758fe0300 · outbound

This paper cites Level generation through large language models.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Level generation through large language models

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:26.784550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:24.528637Z digest=sha256:81f667af4b40a53487bbfe07fb928a4d90bb9791c6f5d77f67dd79b67a3f6231

Observation d45cc9be-b76e-48ae-a8cd-6fe998af2b01 · outbound

This paper cites Czarnecki, Micha \"e l Mathieu, Andrew Dudzik, Junyoung Chung, David H.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Czarnecki, Micha \"e l Mathieu, Andrew Dudzik, Junyoung Chung, David H

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T16:47:24.609668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:47:24.609668Z digest=sha256:c95f4c4ec39bd52b75ce370e778c0380d11a5f59810c97579baf2014e5cad26c

Observation 8a744cd5-ed2f-4375-bc04-c555881b23cd · outbound

This paper cites POET : open-ended coevolution of environments and their optimized solutions.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models POET : open-ended coevolution of environments and their optimized solutions

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:26.588323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:24.684186Z digest=sha256:16bccf1ebad7864a0926f2dc70cbe010c8722785b51b0b0f21d40362f2cdc868

Observation 17228f76-73e4-499d-b445-173927c2aa49 · outbound

This paper cites Enhanced POET : Open-ended reinforcement learning through unbounded invention of learning challenges and their solutions.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Enhanced POET : Open-ended reinforcement learning through unbounded invention of learning challenges and their solutions

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:26.395049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:24.750644Z digest=sha256:2fee2010da551dfc0459afa5f430856af33fcaf815ebcc29c21c6bf2a1be0984

Observation c70a97ca-4e45-4523-bd9d-2521151e04d3 · outbound

This paper cites RoboGen : Towards unleashing infinite data for automated robot learning via generative simulation.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models RoboGen : Towards unleashing infinite data for automated robot learning via generative simulation

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:26.218691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:24.829471Z digest=sha256:501977ba12beafe17172aed07523747251fda66cba5e839d92f8f29c168e9ec0

Observation 86a77f62-0597-488d-a236-d7dec3c40529 · outbound

This paper cites Holodeck: Language guided generation of 3d embodied ai environments.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Holodeck: Language guided generation of 3d embodied ai environments

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:25.968915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:24.906904Z digest=sha256:18343e456fa1b74859b2bb6e160d835199ceffebce83f0114474d5bc8d4dc136

Observation adb8e1fd-cd7f-4178-8339-b599ca31d48b · outbound

This paper cites Envgen: Generating and adapting environments via LLMs for training embodied agents.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Envgen: Generating and adapting environments via LLMs for training embodied agents

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:25.782840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:24.995861Z digest=sha256:22ce8250d58f3157ac7941a6a56d942546503cb89130091aa049cb43eb92185e

Observation 417a633d-6f68-46da-9c0c-b78168bae041 · outbound

This paper cites Automatic playtesting for game parameter tuning via active learning.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models Automatic playtesting for game parameter tuning via active learning

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:47:25.604181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-06T16:47:25.087001Z digest=sha256:72281ec38c4a27756f9808033e530256822e676f39b190e5a7687d8824cd955f

Observation 84cbfdcd-6a67-49fe-9e04-1c53f0ef1a97 · outbound

This paper cites write newline.

Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models write newline

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T16:47:25.181509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:47:25.181509Z digest=sha256:9995521157eeb0ba7a8482e7cbcf1ba06a70900813bb5b7019bb033b36b6f036

Pith citing papers

No inbound Pith citation observations are available.