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Paper Citation Record · LEDGER

Model-based Lookahead Reinforcement Learning

As of 16 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:1908.06012.

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

pith.paper-citation-record.v1
1908.06012 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:17:37.396552Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

45 of 45 outbound references displayed

  • verified exact0
  • verified fuzzy36
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 776294e9-624a-46b1-b34f-dec4ae894125 · outbound

This paper cites P., Bertsekas, D.

Model-based Lookahead Reinforcement Learning P., Bertsekas, D

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation fabf6bcb-aa9a-48b9-bbd0-ee0dd77e7150 · outbound

This paper cites Openai gym, 2016.

Model-based Lookahead Reinforcement Learning Openai gym, 2016

Reference 2

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 79be8fd6-875e-4cf9-8702-40e5ff0e7197 · outbound

This paper cites Sample-efficient reinforcement learning with stochastic ensemble value expansion.

Model-based Lookahead Reinforcement Learning Sample-efficient reinforcement learning with stochastic ensemble value expansion

Reference 3

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 663cb465-4bec-4723-a978-1b559c5243f4 · outbound

This paper cites an unresolved cited work.

Model-based Lookahead Reinforcement Learning Unresolved cited work

Reference 4

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 253a75bb-e7f7-4f74-a597-59d921778c19 · outbound

This paper cites Path integral guided policy search.

Model-based Lookahead Reinforcement Learning Path integral guided policy search

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation db5b2ffc-cfc0-4def-854a-540962279506 · outbound

This paper cites Deep reinforcement learning in a handful of trials using probabilistic dynamics models.

Model-based Lookahead Reinforcement Learning Deep reinforcement learning in a handful of trials using probabilistic dynamics models

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation baaf0c54-ea46-4b32-8d0b-f287051b7d20 · outbound

This paper cites Model-Based Reinforcement Learning via Meta-Policy Optimization.

Model-based Lookahead Reinforcement Learning Model-Based Reinforcement Learning via Meta-Policy Optimization

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 419700fa-9bdc-4041-8247-5369737e0ac6 · outbound

This paper cites and Rasmussen, C.

Model-based Lookahead Reinforcement Learning and Rasmussen, C

Reference 8

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 56bfb4ff-688c-4536-908c-472cd95ce25e · outbound

This paper cites S., Landau, S., Leese, M., and Stahl, D.

Model-based Lookahead Reinforcement Learning S., Landau, S., Leese, M., and Stahl, D

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation f18e2050-0ec2-43d4-b79d-1a4833bbc2ea · outbound

This paper cites Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning.

Model-based Lookahead Reinforcement Learning Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning

Reference 10

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Observation 17609a03-51e6-4ea6-ac2e-5624f0034d74 · outbound

This paper cites E., Prett, D.

Model-based Lookahead Reinforcement Learning E., Prett, D

Reference 11

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 8b727540-6c4d-4ceb-947c-3d31e4fce761 · outbound

This paper cites Continuous deep q-learning with model-based acceleration.

Model-based Lookahead Reinforcement Learning Continuous deep q-learning with model-based acceleration

Reference 12

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0d1db2bb-987b-4666-b769-6a848141db83 · outbound

This paper cites and Boedecker, J.

Model-based Lookahead Reinforcement Learning and Boedecker, J

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 62f1c7ac-bbd8-4ffc-9363-3849a644eb33 · outbound

This paper cites and Deisenroth, M.

Model-based Lookahead Reinforcement Learning and Deisenroth, M

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5358cb5e-add2-4517-92d0-88e34577ed48 · outbound

This paper cites an unresolved cited work.

Model-based Lookahead Reinforcement Learning Unresolved cited work

Reference 15

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5616f29b-bf39-4dec-a9f4-6b963d9b0ceb · outbound

This paper cites Model-ensemble trust-region policy optimization.

Model-based Lookahead Reinforcement Learning Model-ensemble trust-region policy optimization

Reference 16

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation a455a082-acb5-44ae-9899-2397c76d6ff5 · outbound

This paper cites and Abbeel, P.

Model-based Lookahead Reinforcement Learning and Abbeel, P

Reference 17

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 8b8bcc0f-1d01-4f8b-b510-07c1bf1bd264 · outbound

This paper cites and Koltun, V.

Model-based Lookahead Reinforcement Learning and Koltun, V

Reference 18

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 75a62b1e-2405-4a33-b68e-ee12129cb0ee · outbound

This paper cites P., Hunt, J.

Model-based Lookahead Reinforcement Learning P., Hunt, J

Reference 19

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation fbae266b-1913-4a45-9076-ca6ab5126c0d · outbound

This paper cites Plan online, learn offline: Efficient learning and exploration via model-based control.

Model-based Lookahead Reinforcement Learning Plan online, learn offline: Efficient learning and exploration via model-based control

Reference 20

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 73cf11d9-66b6-44a8-9c0c-bdf1439f05cd · outbound

This paper cites Human-level control through deep reinforcement learning.

Model-based Lookahead Reinforcement Learning Human-level control through deep reinforcement learning

Reference 21

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation a1865dd4-34dd-4762-b6dd-ee2de984ae6d · outbound

This paper cites Asynchronous methods for deep reinforcement learning.

Model-based Lookahead Reinforcement Learning Asynchronous methods for deep reinforcement learning

Reference 22

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Observation c68fccc3-3412-44ce-b418-421eb2ef496f · outbound

This paper cites S., and Levine, S.

Model-based Lookahead Reinforcement Learning S., and Levine, S

Reference 23

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Observation d4d28720-0592-4490-a536-5e382e40fa1d · outbound

This paper cites Value prediction network.

Model-based Lookahead Reinforcement Learning Value prediction network

Reference 24

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Observation ac5f6293-98cb-4644-be0e-142b86ac56b5 · outbound

This paper cites Temporal difference models: Model-free deep RL for model-based control.

Model-based Lookahead Reinforcement Learning Temporal difference models: Model-free deep RL for model-based control

Reference 25

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation f1718961-02c7-49f5-8569-33c92c5bf7aa · outbound

This paper cites Imagination-augmented agents for deep reinforcement learning.

Model-based Lookahead Reinforcement Learning Imagination-augmented agents for deep reinforcement learning

Reference 26

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Observation 39317062-92d7-4dfb-94ff-e2981f9a1b85 · outbound

This paper cites an unresolved cited work.

Model-based Lookahead Reinforcement Learning Unresolved cited work

Reference 27

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation a9447858-dad8-455c-840a-2e3088c36866 · outbound

This paper cites The cross-entropy method for combinatorial and continuous optimization.

Model-based Lookahead Reinforcement Learning The cross-entropy method for combinatorial and continuous optimization

Reference 28

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Observation 206744e1-bfc8-4557-a0f1-b9801517f350 · outbound

This paper cites Trust region policy optimization.

Model-based Lookahead Reinforcement Learning Trust region policy optimization

Reference 29

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation bb6bb807-7553-4ba6-968b-46024598ae29 · outbound

This paper cites High-dimensional continuous control using generalized advantage estimation.

Model-based Lookahead Reinforcement Learning High-dimensional continuous control using generalized advantage estimation

Reference 30

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5b4a165f-b097-4e28-a023-39fa80f1ef2a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Model-based Lookahead Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 31

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:17:37.346297Z digest=sha256:eece0410085b4b12066a4b6a8018c8b59ab9dde65269fbc47b62fe3fdc8684ae

Observation 1daab8d8-610c-45b8-87a9-8c9881af384a · outbound

This paper cites S., and Müller, M.

Model-based Lookahead Reinforcement Learning S., and Müller, M

Reference 32

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 04afc63b-720a-4d19-be61-ed2d927076be · outbound

This paper cites J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V ., Lanctot, M., et al.

Model-based Lookahead Reinforcement Learning J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V ., Lanctot, M., et al

Reference 33

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation e847c61d-8b81-484e-982a-f3fda0f64d4d · outbound

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Model-based Lookahead Reinforcement Learning Unresolved cited work

Reference 34

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 38e879ad-ee36-4b66-8541-fa97091598cc · outbound

This paper cites an unresolved cited work.

Model-based Lookahead Reinforcement Learning Unresolved cited work

Reference 35

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.361972Z digest=sha256:b74ed5b8a0c13c55328c60f82adb672bccffffd479b735527d818ad1650a0a33

Observation 8ce5b5d7-cbcd-4d57-92c7-81690b31f1fa · outbound

This paper cites S., McAllester, D.

Model-based Lookahead Reinforcement Learning S., McAllester, D

Reference 36

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raw_fallback, observed 2026-08-14T13:17:37.560709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.365475Z digest=sha256:346d634a00e9de05f225fdcacd7b11c913ffdc2993a53c1717fecffd35ad68ef

Observation d841f841-efcc-425f-a60a-f814578cc467 · outbound

This paper cites S., Szepesvári, C., Geramifard, A., and Bowling, M.

Model-based Lookahead Reinforcement Learning S., Szepesvári, C., Geramifard, A., and Bowling, M

Reference 37

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raw_fallback, observed 2026-08-14T13:17:37.550369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.368753Z digest=sha256:096a6b2757f73a7abd762d4a8017df7e16ee2c24bbcf582129fa1fd3d09d52a0

Observation 48f487be-f315-421f-89be-0fea53bf9a3f · outbound

This paper cites Value iteration networks.

Model-based Lookahead Reinforcement Learning Value iteration networks

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:17:37.539359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.372152Z digest=sha256:5add67f5395d10324175cd00e59a778bcba718a3dd904dc325a9c318e38c2ec3

Observation af888445-fc10-4297-ba8d-c89d6c3db530 · outbound

This paper cites Synthesis and stabilization of complex behaviors through online trajectory optimization.

Model-based Lookahead Reinforcement Learning Synthesis and stabilization of complex behaviors through online trajectory optimization

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:17:37.527957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.376395Z digest=sha256:92e48318a7da329948b8e7480e518caf8542a77a3150e86f6f2cef08d2cb137e

Observation de43765c-0643-4f15-9614-49ef7830ea3d · outbound

This paper cites Control-limited differential dynamic programming.

Model-based Lookahead Reinforcement Learning Control-limited differential dynamic programming

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:17:37.515660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.379869Z digest=sha256:68466b756d2fa9de7c65b5a6140073c41efbc6f74f1195adcc1edb3a3ec87b3e

Observation 3eadc33b-c3f6-455d-9ec8-dd2eba3fa775 · outbound

This paper cites and Li, W.

Model-based Lookahead Reinforcement Learning and Li, W

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:17:37.502924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.383098Z digest=sha256:80f266044a9d079b3084d127d612265827a0a6d1cd9834ab8769374ddb20e272

Observation 53a07cd6-27fe-4312-952c-055db9881305 · outbound

This paper cites Mujoco: A physics engine for model-based control.

Model-based Lookahead Reinforcement Learning Mujoco: A physics engine for model-based control

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:17:37.492279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.386536Z digest=sha256:8417207e3d24584a10572ff200cd68188ef30aa366348b582ded469a6339fa91

Observation 353316e4-5ba0-4ae4-9ea6-1e772cb52d01 · outbound

This paper cites M., Boots, B., and Theodorou, E.

Model-based Lookahead Reinforcement Learning M., Boots, B., and Theodorou, E

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:17:37.480079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.389840Z digest=sha256:34a6ee32ae7a2c0b0781e22853f2ea9e4e31e8374922bd4fccbbf0ebc251cd40

Observation 5759920e-d39d-4673-8b30-067003c84a6f · outbound

This paper cites an unresolved cited work.

Model-based Lookahead Reinforcement Learning Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:17:37.468351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.393125Z digest=sha256:fa9830e9783bb45081eb5550aff547682d390bc0d90413144ed29b02986dd418

Observation c0b22320-15d7-462f-8600-aa8f9b155c09 · outbound

This paper cites Learning deep control policies for autonomous aerial vehicles with mpc-guided policy search.

Model-based Lookahead Reinforcement Learning Learning deep control policies for autonomous aerial vehicles with mpc-guided policy search

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:17:37.457788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:17:37.396552Z digest=sha256:ed98097220d046083e0dc965199763a4da518a8e9be862716f295f801f603be2

Pith citing papers

No inbound Pith citation observations are available.