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Paper Citation Record · LEDGER

Learning Game-Playing Agents with Generative Code Optimization

As of 20 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2508.19506.

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

pith.paper-citation-record.v1
2508.19506 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:56:09.735750Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T16:45:52.375209Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

  • verified exact1
  • verified fuzzy4
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation faf427d6-891f-4f44-8b46-ce04328ad008 · outbound

This paper cites Can You Improve My Code? Optimizing Programs with Local Search.

Learning Game-Playing Agents with Generative Code Optimization Can You Improve My Code? Optimizing Programs with Local Search

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-15T16:56:09.985863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:56:09.646710Z digest=sha256:3a0956f076b3747a43ca49e3e3a7b9c333ba1772a5a05c6c80739fdd1aa8dee3

Observation 45a3fb05-ac12-4e63-93a2-053416057d0a · outbound

This paper cites an unresolved cited work.

Learning Game-Playing Agents with Generative Code Optimization Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-15T16:56:10.054865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:56:09.680384Z digest=sha256:ab7a21843bfbedc2b91ef5007aaade4c88a39aee15f29a1cc69acc0b652fa5ed

Observation 3a5ff651-88e5-44e0-90d1-65417051c023 · outbound

This paper cites LangProp: A code optimization framework using Large Language Models applied to driving.

Learning Game-Playing Agents with Generative Code Optimization LangProp: A code optimization framework using Large Language Models applied to driving

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.684492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.684492Z digest=sha256:24a2c5a668d6cd31b52f3244c722fce7a2f76019229a136694073093a5f99893

Observation 74670a62-f628-4c59-9872-9ef97c650d83 · outbound

This paper cites Playing nethack with llms: Potential & limitations as zero-shot agents.

Learning Game-Playing Agents with Generative Code Optimization Playing nethack with llms: Potential & limitations as zero-shot agents

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:56:10.038127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:56:09.689855Z digest=sha256:71576c5e8c821a4015aa0a474fe9bb71c7f004bc6ad39c69cd71c9e5a10a8bce

Observation feb6d4d0-2d94-4a09-95b2-12fa7a79d204 · outbound

This paper cites Model-Based Reinforcement Learning for Atari.

Learning Game-Playing Agents with Generative Code Optimization Model-Based Reinforcement Learning for Atari

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.694824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.694824Z digest=sha256:45b85b3ff3ce4dc9f1c870883824d919973ad59589e86d1ea1eb0b5dea5b2a59

Observation 30326855-00f8-4aa6-9a74-8cf72b9b2357 · outbound

This paper cites Crafting papers on machine learning.

Learning Game-Playing Agents with Generative Code Optimization Crafting papers on machine learning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.705039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.705039Z digest=sha256:0ffb6005d8f9404b8acd94d791c6c378bfb5ad1ea8ece424a75a16ec94f03c98

Observation 9da6f113-44cb-438d-8d40-7e6434ef3c06 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Learning Game-Playing Agents with Generative Code Optimization Proximal Policy Optimization Algorithms

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.716423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.716423Z digest=sha256:a2447bf991a013109b2a96e88032cd9cd53e9f63fd6da79b8bcee31db4ee6a2a

Observation 82602e5c-cd67-40d4-a674-33c4b194d83b · outbound

This paper cites Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting.

Learning Game-Playing Agents with Generative Code Optimization Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.720002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.720002Z digest=sha256:5f43dc507ceefa82e9dd030aa96155e48a7f4fae155eca9606d535d61067b0b0

Observation 64013453-4c08-4135-aea7-d53296b57965 · outbound

This paper cites Playing games with Large language models: Randomness and strategy.

Learning Game-Playing Agents with Generative Code Optimization Playing games with Large language models: Randomness and strategy

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.723764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.723764Z digest=sha256:348267797777927b685120be4288033f46fe9ce7370815e2130e1e47386981df

Observation 95e97c33-4a92-41de-8b97-01c23c47cff5 · outbound

This paper cites S., Wei, Y ., and Zhang, L.

Learning Game-Playing Agents with Generative Code Optimization S., Wei, Y ., and Zhang, L

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:56:10.016069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:56:09.731775Z digest=sha256:8c32f0233294bf66e2423d5c3cd74e5a94074608148d989f096c90ef6bfa7435

Observation f557ce97-98b1-400b-a41b-da19ba84e38c · outbound

This paper cites Atari Game Setup Pong In Pong, the player controls a paddle on the right side of the screen to deflect the ball into the enemy’s goal.

Learning Game-Playing Agents with Generative Code Optimization Atari Game Setup Pong In Pong, the player controls a paddle on the right side of the screen to deflect the ball into the enemy’s goal

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:56:10.001049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:56:09.735750Z digest=sha256:f0743d79bc750aba6a9f349ff276e8e0896c9a0772b0c9e1fdd436002974173e

Observation fc58f2e3-1f2a-41ce-9b32-08623813e8a6 · outbound

This paper cites Mnih, V ., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., and Riedmiller, M.

Learning Game-Playing Agents with Generative Code Optimization Mnih, V ., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., and Riedmiller, M

Reference 1976

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.708840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.708840Z digest=sha256:09efe7af763e59fa3552d02e72f5853d13d948aeda05ff26db4eb049b63f2192

Observation 8a0f2c1a-1f39-4dad-8c3e-575bd2bd7083 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Learning Game-Playing Agents with Generative Code Optimization Evaluating Large Language Models Trained on Code

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.656512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.656512Z digest=sha256:99825a02b6a50eb8994897b183ba708360c2da9cf3de786d85442d5205a73641

Observation 081ea4d6-37de-4292-a759-0a58cfe323ea · outbound

This paper cites Game-theoretic LLM: Agent Workflow for Negotiation Games.

Learning Game-Playing Agents with Generative Code Optimization Game-theoretic LLM: Agent Workflow for Negotiation Games

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.676323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.676323Z digest=sha256:b60a0a50936d226cec38eeefbfb850ea76128925d82de3d259267ebbcbd39215

Observation 05a9dd97-c0b8-4eed-b876-dfefb73d90f9 · outbound

This paper cites Pok\'eChamp: an Expert-level Minimax Language Agent.

Learning Game-Playing Agents with Generative Code Optimization Pok\'eChamp: an Expert-level Minimax Language Agent

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.700244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.700244Z digest=sha256:0eda0bbb54c44c9308dc52c77778cbd9f2b6bd819b8344811606bdd302b9a8bd

Observation 0146c2a9-f327-41be-9336-86d2b46eb578 · outbound

This paper cites Distributed prior- itized experience replay.

Learning Game-Playing Agents with Generative Code Optimization Distributed prior- itized experience replay

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:56:10.069225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:56:09.672258Z digest=sha256:babc36b799930d2f336647a643dc8d8345e51f769dd75eb07ed3cee62327f7f6

Observation 0de09d53-048b-483f-8b09-7ed9449e537f · outbound

This paper cites Mastering Atari with Discrete World Models.

Learning Game-Playing Agents with Generative Code Optimization Mastering Atari with Discrete World Models

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.666539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.666539Z digest=sha256:c7eabdda2140f6a979266f83c9881bce8edf4a17cded4c4ecaa2514574338b4e

Observation 8848344a-f9e7-45e8-b316-a19031198017 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Learning Game-Playing Agents with Generative Code Optimization Code Llama: Open Foundation Models for Code

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.712742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.712742Z digest=sha256:c60d8d91c5e47d30a204d4141697c731025269c56f5b9a19accbf068036cc1bd

Observation 46ec2b2d-ff89-4a7c-86d2-9d641141b874 · outbound

This paper cites Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation.

Learning Game-Playing Agents with Generative Code Optimization Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.652168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.652168Z digest=sha256:1f5cb4ed2b4d197a80ebdd8561fb801db11beb981a96ddd41dca08f8a22ea49a

Observation 5fcb0ffe-c254-4fa9-8351-9d06829507fa · outbound

This paper cites an unresolved cited work.

Learning Game-Playing Agents with Generative Code Optimization Unresolved cited work

Reference 2024

Resolution
unresolved
raw_fallback, observed 2026-08-15T16:56:10.085026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:56:09.661425Z digest=sha256:fe8e426281d94c4e2efa23db42f3ec2c2d1eaf7793405546db7417d824d98b3c

Observation 3b85502a-098a-44f9-957b-0450883caf95 · outbound

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

Learning Game-Playing Agents with Generative Code Optimization Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:09.727511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:09.727511Z digest=sha256:cb3ad6bed06700454aa15c7b1f48c5de1cc84879c38f9c786a5ee04c917dee4e

Pith citing papers

Observation 94e76f4e-6b06-4507-96fc-82246f1f154f · inbound

Overcoming the Weakest-Link Effect in LLM-Driven Program Optimization via Heterogeneous Edit Recombination cites this paper.

Overcoming the Weakest-Link Effect in LLM-Driven Program Optimization via Heterogeneous Edit Recombination Learning Game-Playing Agents with Generative Code Optimization

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-03T16:45:52.375209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T16:45:52.375209Z digest=sha256:ce9e6b1fe202b9e743b365ec159707df7aa2cf24470696bb114bb02b97af528e