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Paper Citation Record · LEDGER

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents

As of 16 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2507.07848.

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

pith.paper-citation-record.v1
2507.07848 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:36:43.205768Z

measured 35 of 35 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T15:01:52.583181Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T11:16:11.205349Z

Reference resolution

34 of 34 outbound references displayed

  • verified exact3
  • verified fuzzy7
  • unresolved22
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 95f26998-1e1a-4156-a40e-5a588965f3ad · outbound

This paper cites Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning

Reference 1

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local_arxiv, observed 2026-08-06T18:36:44.309466Z

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

source=pdf_text observed=2026-08-06T18:36:40.623694Z digest=sha256:4e9861015f77756caca5aabb4aa3b0436a958815cf0308a4180deb91f07f7d18

Observation f6f4d27e-7671-4d63-9e53-ab4d21e4f298 · outbound

This paper cites an unresolved cited work.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Unresolved cited work

Reference 2

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Observation 104725c9-b729-4cfc-8cd3-4f41033a0f4a · outbound

This paper cites Bastani, Y.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Bastani, Y

Reference 3

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Observation 27e70747-2d56-420a-baef-1cbe2d3e9fd6 · outbound

This paper cites an unresolved cited work.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-06T18:36:40.793229Z digest=sha256:1bf43634011ec13a4a29cd9eb3c514e9263122f147c1bef4af9ef7c9fccfc231

Observation c0e22369-6a5d-41d8-b013-eff8da762ef3 · outbound

This paper cites XGBoost: A Scalable Tree Boosting System.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents XGBoost: A Scalable Tree Boosting System

Reference 6

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source=pdf_text observed=2026-08-06T18:36:40.967804Z digest=sha256:0c0464ef7c97013df811cff1de6d3a5d61ce03a4a33ac853226c38e696e1ff58

Observation 23ecd545-926a-4970-8040-937706c6b044 · outbound

This paper cites an unresolved cited work.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Unresolved cited work

Reference 7

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source=pdf_text observed=2026-08-06T18:36:41.043766Z digest=sha256:47ac08146bdc027e3130ed8fbfbd7a98097613e2bf7fe60cc8dd598cfdca7971

Observation 489c0ef0-f354-42e1-a11a-235f990ce760 · outbound

This paper cites Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey

Reference 8

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source=pdf_text observed=2026-08-06T18:36:41.113929Z digest=sha256:01f81f2edb9504eba6afff7f9bc28dcfe78cfd3f22b1bdb64d41228be028e4cf

Observation 16701200-0bf9-4c6f-9939-32dcf01d684c · outbound

This paper cites Ernst, P.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Ernst, P

Reference 9

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Observation 656f1846-0d53-4fbf-813d-e5f41bd200be · outbound

This paper cites Limit Order Books.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Limit Order Books

Reference 10

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source=pdf_text observed=2026-08-06T18:36:41.329870Z digest=sha256:4366f66ebeeeae272c3cb492e0d0a2cebf8794592b6779b1cede46c49aeea249

Observation 6ba3920d-a826-461d-bcb6-cbd1bffb587c · outbound

This paper cites Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Reference 11

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Observation e656d7bd-221f-4f68-a2ca-59e5cc2fcdf0 · outbound

This paper cites Generative Adversarial Imitation Learning.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Generative Adversarial Imitation Learning

Reference 12

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source=pdf_text observed=2026-08-06T18:36:41.470280Z digest=sha256:885b605b3b8567b42f85553da7adfe33e2be08f692d3d3b6f50c59c31a6f5b0a

Observation 77dba5d7-122a-4f18-b8ce-95e62973adcf · outbound

This paper cites Scaling Laws for Neural Language Models.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Scaling Laws for Neural Language Models

Reference 13

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source=pdf_text observed=2026-08-06T18:36:41.556842Z digest=sha256:e04326f963408b12c76848a7b540009214519393691f71af20492cf330eb987b

Observation f7b17c13-5645-4e65-b605-f3a140014281 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Adam: A Method for Stochastic Optimization

Reference 14

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source=pdf_text observed=2026-08-06T18:36:41.595975Z digest=sha256:838e7df900cd016f13ceabb2766e61ded7169eddc6ebe31dcc7cf6b62f96aee1

Observation 47703804-323e-4b65-ac94-1eba4ec94ead · outbound

This paper cites Likmeta, A.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Likmeta, A

Reference 15

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source=pdf_text observed=2026-08-06T18:36:41.687392Z digest=sha256:7871ffe35e9a8f3c2f31d6f7200eaf63de79e84f9872aa3e60cabeb0f12e7179

Observation 70293423-5513-4844-baa7-0a4d62ec54de · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents A Unified Approach to Interpreting Model Predictions

Reference 17

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source=pdf_text observed=2026-08-06T18:36:41.924890Z digest=sha256:8314dbd88e2fb0b608028a5df3fcc00206b7a95acd78add1f23ed7edb417cdb2

Observation bacba575-7fc9-4467-99da-ea6302ffcf9b · outbound

This paper cites Madumal, T.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Madumal, T

Reference 18

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

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Observation c154b661-19aa-4164-b508-bee8ded4520d · outbound

This paper cites Milani, N.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Milani, N

Reference 19

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source=pdf_text observed=2026-08-06T18:36:42.087560Z digest=sha256:686949a566d1d3878b927f10b71c00a3b2d03081f93958430cdb9b004d029873

Observation 6c056548-b9df-4bf5-807d-18451ced58ad · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Playing Atari with Deep Reinforcement Learning

Reference 20

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Observation b4690ba5-7521-406e-aae4-ab9fa632357d · outbound

This paper cites Pirotta, M.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Pirotta, M

Reference 21

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

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Observation f085db74-bd2b-42a6-a196-1ac52e376e34 · outbound

This paper cites Raffin, A.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Raffin, A

Reference 22

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

source=pdf_text observed=2026-08-06T18:36:42.358506Z digest=sha256:afa1172f914bcfff6008408072c0475711e6fef515fc6beba01c9ddd117d377e

Observation cb27aa3c-4d3d-4bda-9c18-0f555ee3d69e · outbound

This paper cites Ross and D.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Ross and D

Reference 23

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

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Observation 486bbe3a-042f-4a19-9e8f-de5fcefde6d3 · outbound

This paper cites A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning

Reference 24

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source=pdf_text observed=2026-08-06T18:36:42.485427Z digest=sha256:f152fdc74b61040c1ba54ce8853a7940c7dade0e75c439c869c49ee518d7fd7f

Observation c55ec9d5-e171-4c49-9c7f-1b1f518d4003 · outbound

This paper cites Policy Distillation.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Policy Distillation

Reference 25

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Observation d18e3e25-e6a1-490b-8443-d6213004d448 · outbound

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"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Unresolved cited work

Reference 26

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source=pdf_text observed=2026-08-06T18:36:42.598639Z digest=sha256:0ead1dee628482be954286f97194fb0153514bdd72525034a533bbc992a803a1

Observation 388688a3-fd09-4b5b-949f-687de9beb5a0 · outbound

This paper cites Silver, A.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Silver, A

Reference 27

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Observation e95d96f0-0bdb-4331-b3d0-b4e332e00e93 · outbound

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"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Unresolved cited work

Reference 28

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Observation f1eb5a81-083f-4518-aecf-1bafe7294808 · outbound

This paper cites an unresolved cited work.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Unresolved cited work

Reference 29

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Observation 089f3cf2-aea5-43ee-9f2f-e3b3a05e0edb · outbound

This paper cites Gymnasium: A Standard Interface for Reinforcement Learning Environments.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Gymnasium: A Standard Interface for Reinforcement Learning Environments

Reference 30

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source=pdf_text observed=2026-08-06T18:36:42.916690Z digest=sha256:27ed68733222c74586fab0514717eb06aee6030245740a2dd33ba716d2f9f3bb

Observation e26d1c88-95fd-4fcf-8e06-47c21d96bc1e · outbound

This paper cites an unresolved cited work.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Unresolved cited work

Reference 32

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source=pdf_text observed=2026-08-06T18:36:43.159262Z digest=sha256:c75fff43b89bfd2657b8ef22a3a296d093e7aff5f1db68c8833ee5da22a4a20b

Observation b86bce2e-9fc8-48d8-aea1-7379b5bca79b · outbound

This paper cites an unresolved cited work.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Unresolved cited work

Reference 33

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source=pdf_text observed=2026-08-06T18:36:43.205768Z digest=sha256:e5854c974b422782efad389ec80318a5d3dbb30b40ea0a2bde525c8b53c59f9d

Observation 87dc3488-3b3b-4306-bec0-a90966db9e2b · outbound

This paper cites Programmatically Interpretable Reinforcement Learning.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Programmatically Interpretable Reinforcement Learning

Reference 35

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source=pdf_text observed=2026-08-06T18:36:43.074284Z digest=sha256:5e6f4d5faa2ed6d926a994eb3a847e4fc4425c7ec293bfd0e9afd9861051fc16

Observation 69b28478-8241-419b-8742-e5a319229a82 · outbound

This paper cites an unresolved cited work.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Unresolved cited work

Reference 2005

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source=pdf_text observed=2026-08-06T18:36:41.267103Z digest=sha256:b157409b71f95d5886ecb7dc2933c00a069950b2085b580f2044030eff42f185

Observation 84856176-ead1-4ab0-afb5-719450b71aec · outbound

This paper cites Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees

Reference 2018

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local_arxiv, observed 2026-08-06T18:36:43.680643Z

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

source=pdf_text observed=2026-08-06T18:36:41.844751Z digest=sha256:000ca76a5fa7a7fd286ba5fd2ff999762a258eff165770e2003022f11cd2783e

Observation e18f7011-50c9-4c5c-a035-9cb088ecb4d3 · outbound

This paper cites Deep Reinforcement Learning for Active High Frequency Trading.

"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents Deep Reinforcement Learning for Active High Frequency Trading

Reference 2021

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Pith citing papers

Observation 7bde5198-5a12-4239-a8ec-c2bba0cf3aba · inbound

Selecting Feature Interactions for Generalized Additive Models by Distilling Foundation Models cites this paper.

Selecting Feature Interactions for Generalized Additive Models by Distilling Foundation Models "So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents

Reference 6

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arxiv_id, observed 2026-05-11T11:16:11.210837Z

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source=pdf_text observed=2026-05-10T15:01:52.583181Z digest=sha256:9ed7ac2314cf2f536202549849f91e5e63f76760e812b234e199d6caaf61a158