Paper Citation Record · LEDGER

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm

As of 15 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2411.08392.

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

pith.paper-citation-record.v1
2411.08392 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:42:27.990775Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

40 of 40 outbound references displayed

verified exact3
verified fuzzy13
unresolved21
parse uncertain0
malformed identifier3
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9db5e72c-000d-4fdf-bc8a-a76ff2677dbf · outbound

This paper cites Deep learning.Nature, 521(7553):436–444, May 2015.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Deep learning.Nature, 521(7553):436–444, May 2015

Reference 1

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Source-reported events for the cited work

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Observation 1f76a717-08c5-4efe-b8ba-bb393663080a · outbound

This paper cites A critical analysis of metrics used for measuring progress in artificial intelligence, 2021.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm A critical analysis of metrics used for measuring progress in artificial intelligence, 2021

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:29.126062Z

Source-reported events for the cited work

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Observation e6ef484c-a886-4cf3-b990-3934fec1514a · outbound

This paper cites Evaluating the quality of machine learning explanations: A survey on methods and metrics.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Evaluating the quality of machine learning explanations: A survey on methods and metrics

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:29.110819Z

Source-reported events for the cited work

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Observation f3e1bd1f-07a7-4946-a3d2-1475d5b68fe9 · outbound

This paper cites Viegas, and Martin Wattenberg.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Viegas, and Martin Wattenberg

Reference 4

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Source-reported events for the cited work

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Observation aafea5cb-0785-4c30-8a17-9b7290bd2d4a · outbound

This paper cites Vega-lite: A grammar of interactive graphics.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Vega-lite: A grammar of interactive graphics

Reference 5

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Source-reported events for the cited work

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Observation 8e8c6770-3994-41d1-b6b8-f1804eb7bd80 · outbound

This paper cites Activis: Visual exploration of industry-scale deep neural network models.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Activis: Visual exploration of industry-scale deep neural network models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:29.096286Z

Source-reported events for the cited work

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Observation eb1c7cac-3de6-4572-bdb3-d95cfe94b270 · outbound

This paper cites Interacting with predictions: Visual inspection of black-box machine learning models.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Interacting with predictions: Visual inspection of black-box machine learning models

Reference 7

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Source-reported events for the cited work

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Observation e004f102-ea43-4407-97d3-9138105c274d · outbound

This paper cites Understanding Neural Networks Through Deep Visualization.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Understanding Neural Networks Through Deep Visualization

Reference 8

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Source-reported events for the cited work

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Observation fde3098f-7d6a-44a1-a288-3924bc839c8c · outbound

This paper cites Machine learning-based approach: global trends, research directions, and regulatory standpoints.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Machine learning-based approach: global trends, research directions, and regulatory standpoints

Reference 9

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Source-reported events for the cited work

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Observation bdb219d2-1fad-41b0-82a3-33feeeeb6b2e · outbound

This paper cites Reinforcement Learning Applications.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Reinforcement Learning Applications

Reference 10

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Source-reported events for the cited work

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Observation 284dd64f-3838-493e-82d1-20a9ac3c9b12 · outbound

This paper cites Illustrat- ing reinforcement learning from human feedback (rlhf).

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Illustrat- ing reinforcement learning from human feedback (rlhf)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:29.081394Z

Source-reported events for the cited work

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Observation 954b9aac-ff98-4934-bf08-1522c62a1824 · outbound

This paper cites Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models

Reference 12

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Source-reported events for the cited work

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Observation 859985c7-f43d-4be1-a9b1-ae0df65581ff · outbound

This paper cites Parkes, and Richard Socher.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Parkes, and Richard Socher

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 222dd36b-d2b3-4337-8ee0-517baf11c3a6 · outbound

This paper cites Reinforcement Learning for Economic Policy: A New Frontier?.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Reinforcement Learning for Economic Policy: A New Frontier?

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29dcb409-d032-4f09-b58f-091a52877c93 · outbound

This paper cites Deep reinforcement learning approaches for global public health strategies for covid-19 pandemic.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Deep reinforcement learning approaches for global public health strategies for covid-19 pandemic

Reference 15

Resolution: verified exact; doi, observed 2026-08-12T21:42:28.089509Z

Source-reported events for the cited work

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Observation 42704388-9be1-4d9d-973c-6a2dd6591840 · outbound

This paper cites Optimising lockdown policies for epidemic control using reinforcement learning: An ai-driven control approach compatible with existing disease and network models.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Optimising lockdown policies for epidemic control using reinforcement learning: An ai-driven control approach compatible with existing disease and network models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:29.066560Z

Source-reported events for the cited work

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Observation 30029c9f-0f2e-4314-9b7f-a7e2170890c9 · outbound

This paper cites Recent Advances in Reinforcement Learning in Finance.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Recent Advances in Reinforcement Learning in Finance

Reference 17

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Source-reported events for the cited work

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Observation 0026f743-2df6-48f8-b127-8f42e33e5168 · outbound

This paper cites Reinforcement learning for clinical decision support in critical care: Comprehensive review.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Reinforcement learning for clinical decision support in critical care: Comprehensive review

Reference 18

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Source-reported events for the cited work

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Observation 34e23c95-795d-438a-abe6-b7f72af752f6 · outbound

This paper cites The loca regret: A consistent metric to evaluate model-based behavior in reinforcement learning.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm The loca regret: A consistent metric to evaluate model-based behavior in reinforcement learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:29.051501Z

Source-reported events for the cited work

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Observation fe33f9d1-653b-4cd7-8db3-1c938b690a3f · outbound

This paper cites Evaluating the performance of reinforcement learning algorithms.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Evaluating the performance of reinforcement learning algorithms

Reference 20

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Source-reported events for the cited work

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Observation 69c7344f-4788-4785-8732-5664cbace844 · outbound

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RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Unresolved cited work

Reference 21

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Source-reported events for the cited work

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Observation 39bf8084-c2bd-4cc1-8b48-55c6be5c706f · outbound

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RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Unresolved cited work

Reference 22

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Observation e04b6840-8601-4394-8b13-2168d95b72be · outbound

This paper cites Challenges in the verification of reinforcement learning algorithms.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Challenges in the verification of reinforcement learning algorithms

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:29.007600Z

Source-reported events for the cited work

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Observation b6eabb43-f3d0-458b-9e4d-46b19e5922f3 · outbound

This paper cites Trans- parency and explanation in deep reinforcement learning neural networks.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Trans- parency and explanation in deep reinforcement learning neural networks

Reference 24

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Observation 10193c46-e58e-4dc2-adaa-b0b1596218f9 · outbound

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RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Unresolved cited work

Reference 25

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Source-reported events for the cited work

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Observation a612a3cd-ebc2-4437-a36f-1f85a382c4c5 · outbound

This paper cites Interestingness elements for explainable reinforce- ment learning: Understanding agents' capabilities and limitations.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Interestingness elements for explainable reinforce- ment learning: Understanding agents' capabilities and limitations

Reference 26

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Source-reported events for the cited work

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Observation b63a38b1-be25-4167-9824-5c04f11c9c8c · outbound

This paper cites Explaining online reinforcement learning decisions of self-adaptive systems.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Explaining online reinforcement learning decisions of self-adaptive systems

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:28.978471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b8526188-b9c9-4a9e-980b-bc14cb63e71e · outbound

This paper cites Dietterich, Rachel Houtman, Claire Mont- gomery, and Ronald Metoyer.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Dietterich, Rachel Houtman, Claire Mont- gomery, and Ronald Metoyer

Reference 28

Resolution: verified exact; doi, observed 2026-08-12T21:42:28.059029Z

Source-reported events for the cited work

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Observation 7a1b7994-7008-47b0-ac56-fa4dcb03916c · outbound

This paper cites Dqnviz: A visual analytics approach to understand deep q-networks.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Dqnviz: A visual analytics approach to understand deep q-networks

Reference 29

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Source-reported events for the cited work

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Observation 70421e0b-b71e-4c50-b128-936bb4aa0764 · outbound

This paper cites Drlviz: Understanding decisions and memory in deep reinforcement learning.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Drlviz: Understanding decisions and memory in deep reinforcement learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:28.963778Z

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Observation 516ce644-29da-4380-ad71-545a19f71ea4 · outbound

This paper cites Collaborative data science, 2015.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Collaborative data science, 2015

Reference 31

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Source-reported events for the cited work

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RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Openai gym, 2016

Reference 32

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Source-reported events for the cited work

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This paper cites Ross, Jongwoo Lim, Ruei-Sung Lin, and Ming-Hsuan Yang.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Ross, Jongwoo Lim, Ruei-Sung Lin, and Ming-Hsuan Yang

Reference 33

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Observation b916f6df-982e-4395-b586-d2ff98312e5a · outbound

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RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Unresolved cited work

Reference 34

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Source-reported events for the cited work

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Observation c021fdb5-9ce6-40b4-92dc-a959581bc288 · outbound

This paper cites Understanding the difficulty of training deep feedforward neural networks.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Understanding the difficulty of training deep feedforward neural networks

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:28.928791Z

Source-reported events for the cited work

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Observation a37b3ad9-54f8-4130-b97d-1c3840a07b7f · outbound

This paper cites Visualizing distortions and recovering topology in continuous projection techniques.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Visualizing distortions and recovering topology in continuous projection techniques

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:28.913417Z

Source-reported events for the cited work

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Observation 19f8ba38-7990-48b7-a924-7df1e35eb693 · outbound

This paper cites Heulot, M.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Heulot, M

Reference 37

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Source-reported events for the cited work

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Observation 24e3c31c-9843-49f2-a636-717cb36544ca · outbound

This paper cites A multidimensional brush for scatterplot data analytics.

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm A multidimensional brush for scatterplot data analytics

Reference 38

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Source-reported events for the cited work

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Observation 9cc316dd-6a41-4632-addc-5a6d491f0642 · outbound

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RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Unresolved cited work

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T21:42:27.985906Z

Source-reported events for the cited work

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Observation 5a4050b4-e545-4a49-95a5-9ba6f9767c8e · outbound

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RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm Visualizing data using t-sne

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:42:28.898204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.