Paper Citation Record · LEDGER

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26

As of 19 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.07498.

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

pith.paper-citation-record.v1
2607.07498 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-09T09:08:14.104220Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

24 of 24 outbound references displayed

verified exact2
verified fuzzy20
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5c4be205-f414-44d0-a084-bba86c3f92e4 · outbound

This paper cites Automated video game testing using synthetic and humanlike agents,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Automated video game testing using synthetic and humanlike agents,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.916723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation de5ef3f2-1a9a-4a03-90e3-4cd8786354ae · outbound

This paper cites Automated play-testing through rl based human-like play-styles generation,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Automated play-testing through rl based human-like play-styles generation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.911198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5c186563-60a5-4ace-898b-c571a551f425 · outbound

This paper cites Augmenting automated game testing with deep rein- forcement learning,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Augmenting automated game testing with deep rein- forcement learning,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.913122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 899641aa-4431-48e2-b98e-f5e03b74cbb8 · outbound

This paper cites Emergent tool use from multi-agent autocurricula,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Emergent tool use from multi-agent autocurricula,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.909058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 846541da-ebc8-4165-9103-81946fe86a0e · outbound

This paper cites Improving playtesting coverage via curiosity driven reinforcement learning agents,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Improving playtesting coverage via curiosity driven reinforcement learning agents,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.920709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cca9e18e-a23e-4628-9b85-e002889c6b94 · outbound

This paper cites Automated gameplay testing and validation with curiosity-conditioned proximal trajectories,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Automated gameplay testing and validation with curiosity-conditioned proximal trajectories,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.922406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 106edc69-2e7e-42c7-8053-cdefe9aa59ca · outbound

This paper cites Discovering policies with DOMiNO: Diversity optimization maintaining near optimality,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Discovering policies with DOMiNO: Diversity optimization maintaining near optimality,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.913452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 73ecc8ab-29b6-471d-9f55-205785a95876 · outbound

This paper cites Available: https://openreview.net/forum? id=kjkdzBW3b8p.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Available: https://openreview.net/forum? id=kjkdzBW3b8p

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.917237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2296dcd6-1530-4913-87d3-9cd931d3db44 · outbound

This paper cites Discovering creative behaviors through du- plex: Diverse universal features for policy exploration,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Discovering creative behaviors through du- plex: Diverse universal features for policy exploration,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.907424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c2e5b2ba-a4c8-47e5-9e73-351249d213b4 · outbound

This paper cites Grandmaster level in starcraft ii using multi-agent reinforcement learning,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Grandmaster level in starcraft ii using multi-agent reinforcement learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.914972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3409aca1-8368-43d5-ad77-e6396f58524a · outbound

This paper cites Outracing champion gran tur- ismo drivers with deep reinforcement learning,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Outracing champion gran tur- ismo drivers with deep reinforcement learning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.918847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8e80f8dc-1702-4875-83d0-7fd826c8dd28 · outbound

This paper cites Automated playtesting with procedural personas through mcts with evolved heuristics,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Automated playtesting with procedural personas through mcts with evolved heuristics,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.900463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 87a1a230-4c72-40a4-9d44-c8e3974a0e1f · outbound

This paper cites Navigation turing test (ntt): Learning to evaluate human-like navigation,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Navigation turing test (ntt): Learning to evaluate human-like navigation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.902092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 740098e4-6fd7-4279-8e24-540150e5a837 · outbound

This paper cites Stanley , editor =.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Stanley , editor =

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-09T09:16:06.673683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0e8db9ca-956e-450e-b36e-9b6fac1f0895 · outbound

This paper cites Illuminating search spaces by mapping elites.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Illuminating search spaces by mapping elites

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-09T09:16:06.700898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7ab1e778-5804-4c9c-9d8e-84ecad2637a6 · outbound

This paper cites Robots that can adapt like animals.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Robots that can adapt like animals

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.907215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2617b097-d43d-4c3c-8db2-e9e1f77fafa1 · outbound

This paper cites Variational intrinsic control,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Variational intrinsic control,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.894031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9e8e45b5-0b43-4c16-b247-3d015b492d23 · outbound

This paper cites Diversity is all you need: Learning skills without a reward function,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Diversity is all you need: Learning skills without a reward function,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.892108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 830aba0e-e976-4acd-a93a-b48abe0a1983 · outbound

This paper cites Successor features for transfer in reinforcement learning,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Successor features for transfer in reinforcement learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.898747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 910ac1d6-362b-4cc9-bbaf-dd5568be7256 · outbound

This paper cites Policy invariance under reward transformations: Theory and application to reward shaping.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Policy invariance under reward transformations: Theory and application to reward shaping

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.888320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 91f57102-47d7-4519-b353-28e5bba13ded · outbound

This paper cites an unresolved cited work.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-07-09T09:16:06.893886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1b2be37c-750a-419c-bd57-43d72fea8cab · outbound

This paper cites Soft actor-critic: Off-policy maximum entropy deep reinforce- ment learning with a stochastic actor,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Soft actor-critic: Off-policy maximum entropy deep reinforce- ment learning with a stochastic actor,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.890293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ca0e207e-3619-4b4c-94ac-29909f7bfe83 · outbound

This paper cites Discrete and Continuous Action Representation for Practical RL in Video Games.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Discrete and Continuous Action Representation for Practical RL in Video Games

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-07-09T09:16:06.703424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 39ca2de1-9a5f-4d76-ba9c-9056b6cf8afb · outbound

This paper cites Some methods of classification and analysis of multivariate observations,.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Some methods of classification and analysis of multivariate observations,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T09:16:06.905768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.