Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:41:13.953628Z
Paper Citation Record · LEDGER
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games
As of 17 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2506.23626.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
14 of 14 outbound references displayed
- verified exact0
- verified fuzzy7
- unresolved5
- parse uncertain0
- malformed identifier1
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f13b1593-9979-4bf9-af18-bb1a1b7a84c6 · outbound
This paper cites an unresolved cited work.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T21:41:16.571140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b3449306-4e61-4056-9538-1e58989b0715 · outbound
This paper cites Instructions.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games Instructions
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:41:16.378885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3a6e5395-af65-4535-bcb8-925621b60483 · outbound
This paper cites • Adjust values to encourage the agent to complete the goal properly rather than remaining close to it.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games • Adjust values to encourage the agent to complete the goal properly rather than remaining close to it
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:41:15.765168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 02429b1e-248e-4587-8aeb-b749060398cd · outbound
This paper cites an unresolved cited work.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T21:41:15.533487Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8cd012bf-5014-47db-a29b-7e198e3d1ee5 · outbound
This paper cites an unresolved cited work.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T21:41:16.179890Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ea1367b6-e3a6-4383-8564-c12a9ee351f8 · outbound
This paper cites • These parameters control the agent’s learning and behavior.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games • These parameters control the agent’s learning and behavior
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:41:15.991458Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3f643437-5a2b-43bd-8a36-28e141c0720b · outbound
This paper cites For instance, if theProblem description is talking about making the agents collide less, but does not refer hitting the fence,do not change the fence collision penalty.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games For instance, if theProblem description is talking about making the agents collide less, but does not refer hitting the fence,do not change the fence collision penalty
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:41:15.336253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d9417170-972f-4942-b930-3069e9e49353 · outbound
This paper cites • The format of the outputmust be identicalto the .txt file.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games • The format of the outputmust be identicalto the .txt file
Reference 10
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-06T21:41:15.161476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 950e8afd-d779-430d-98f7-bdd64b67600c · outbound
This paper cites in the least amount of time steps.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games in the least amount of time steps
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:41:14.974683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9e02ff12-8e3c-4c01-a2f2-edbacc489886 · outbound
This paper cites an unresolved cited work.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T21:41:14.763880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 59b48f51-89e1-4354-b052-6931d15109b6 · outbound
This paper cites Try to be creative with the solution, ie.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games Try to be creative with the solution, ie
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:41:14.577985Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2f60979a-0dca-4fcd-9b60-c098dc3bde44 · outbound
This paper cites Your output should be the updated reward function file only.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games Your output should be the updated reward function file only
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:41:14.422955Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c3808800-ed00-446a-8938-fb0675132a38 · outbound
This paper cites Yan Zheng, Xiaofei Xie, Ting Su, Lei Ma, Jianye Hao, Zhaopeng Meng, Yang Liu, Ruimin Shen, Yingfeng Chen, and Changjie Fan.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games Yan Zheng, Xiaofei Xie, Ting Su, Lei Ma, Jianye Hao, Zhaopeng Meng, Yang Liu, Ruimin Shen, Yingfeng Chen, and Changjie Fan
Reference 2023
- Resolution
- metadata mismatch
- raw_fallback, observed 2026-08-06T21:41:14.245278Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1bd7b80f-7613-4173-ba96-9553b70eddc3 · outbound
This paper cites OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code.
Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:41:10.068318Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.