Pith. sign in

Paper Citation Record · LEDGER

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking

As of 16 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:1908.04573.

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

pith.paper-citation-record.v1
1908.04573 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:42:46.233335Z

measured 35 of 35 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

35 of 35 outbound references displayed

  • verified exact0
  • verified fuzzy24
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8edd8415-e090-4fc0-8768-de7cd50070c6 · outbound

This paper cites Journal of Economic Dynamics and Control , 27(11):2207 – 2218, 2003.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Journal of Economic Dynamics and Control , 27(11):2207 – 2218, 2003

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.678473Z

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=2026-08-14T13:42:46.090861Z digest=sha256:0975c8578f19c6dd383b56af68764e66ba2dad48e9cfdf00707ffc839dfa2200

Observation 54dd1678-8039-454c-a204-fb8f519e9f2f · outbound

This paper cites an unresolved cited work.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:42:46.666863Z

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=2026-08-14T13:42:46.095439Z digest=sha256:594e2e75026fce966b74d612892932e5b0312b94a6f2a4d08c8a1caeab4e0126

Observation 12880038-bed2-4c9f-8026-ae94f05958d4 · outbound

This paper cites Deep Reinforcement Learning framework for Autonomous Driving.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Deep Reinforcement Learning framework for Autonomous Driving

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-14T13:42:46.099877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:42:46.099877Z digest=sha256:673b12a33833ea29dd47be57d319d91e1c2a3413bb54953b332700b52bccc0a7

Observation 370b9111-e8aa-49ce-bdfc-b87cad7b422f · outbound

This paper cites Learning exploration/exploitation strategies for single trajectory reinforcement learning.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Learning exploration/exploitation strategies for single trajectory reinforcement learning

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.655422Z

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=2026-08-14T13:42:46.104836Z digest=sha256:014789232071c2a340db6b866ed616a82311b40013c91e7b5f895632ecd21133

Observation 6798d111-1c15-4662-aca0-0f115115476c · outbound

This paper cites Papadimitriou and John N.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Papadimitriou and John N

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.644069Z

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=2026-08-14T13:42:46.109719Z digest=sha256:def2128784fb80185271653a9ab7d4c6af9893fbd1f0d6c6f0b87552f46623ba

Observation de953e4b-b0bf-4ad4-b134-096eb2d0d40a · outbound

This paper cites Littman, and Andrew W.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Littman, and Andrew W

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-14T13:42:46.113490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:42:46.113490Z digest=sha256:aa3057f640aeb817187f90ce2919e503ac3afb847daee22bf7a4bc06ef2405b9

Observation 4679c160-8724-4c08-9355-4d05b7468b00 · outbound

This paper cites Foerster, Yannis M.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Foerster, Yannis M

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.621725Z

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=2026-08-14T13:42:46.118299Z digest=sha256:3c2bcb6fc0ef6e4cf3cd6601434420af7d003525ad34edb8820695d4ede13046

Observation fbceb09e-f765-4f38-8f17-39fe0c10e8a0 · outbound

This paper cites Multi-agent actor-critic for mixed cooperative-competitive environments.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Multi-agent actor-critic for mixed cooperative-competitive environments

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.606911Z

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=2026-08-14T13:42:46.121766Z digest=sha256:009f3db920f8351518ebb7d2ff9c2b48ae633a23b0a7a9602646360d707e48b3

Observation a86e81aa-e180-4c75-9301-66acfc9d82ea · outbound

This paper cites Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, and Shimon Whiteson.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, and Shimon Whiteson

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.592899Z

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=2026-08-14T13:42:46.125237Z digest=sha256:15fdacdf8e999c303633cd68d990cc10cb1bbe69d2201abeb5c07fd302827bf1

Observation 9475dbb1-f6a8-4ab0-a282-63396384c439 · outbound

This paper cites Counterfactual data- fusion for online reinforcement learners.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Counterfactual data- fusion for online reinforcement learners

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.580700Z

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=2026-08-14T13:42:46.130442Z digest=sha256:788683b3e3f9e4729ebb1ea372775a4a54b4921906d3e855a801b97b3cfe9630

Observation 63e98418-2dd5-4b6b-8cd5-cb4556658431 · outbound

This paper cites Gupta, Maxim Egorov, and Mykel J.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Gupta, Maxim Egorov, and Mykel J

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.568773Z

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=2026-08-14T13:42:46.133929Z digest=sha256:86934915c29aa880714c3530410bfacef7c71cd37ea42ee1ce52200b30a6ab56

Observation e24adfeb-cd8b-490b-8edd-61daded97683 · outbound

This paper cites Reinforcement Learning and Markov Decision Processes , pages 3–42.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Reinforcement Learning and Markov Decision Processes , pages 3–42

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.555907Z

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=2026-08-14T13:42:46.137600Z digest=sha256:41740b7b7dcaf62cb2befe93a3938ac3e7e5a47e8a898b719e075827800c1307

Observation 362d6500-549b-4b35-8e84-aedd8ec5a9bf · outbound

This paper cites Hausknecht and Peter Stone.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Hausknecht and Peter Stone

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.543764Z

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=2026-08-14T13:42:46.141645Z digest=sha256:b7adf6dceeb6849a22807cb71df3a3fd56ed1483c3a866b2e9a3e576fa3cf949

Observation 9ef5cc7b-dd91-49ac-a099-09a709ca417e · outbound

This paper cites Reinforcement learning to play an optimal nash equilibrium in team markov games.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Reinforcement learning to play an optimal nash equilibrium in team markov games

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.529199Z

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=2026-08-14T13:42:46.146634Z digest=sha256:3d3f02d76d8d6f947c5ff2b9d0245ebf8390c2378d749ca7928605365e021b6a

Observation a27245f5-2580-44cb-b65a-df97e1580644 · outbound

This paper cites An algorithm for distributed reinforcement learning in cooperative multi-agent systems.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking An algorithm for distributed reinforcement learning in cooperative multi-agent systems

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.513247Z

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=2026-08-14T13:42:46.150271Z digest=sha256:adc0e1282523940393efd378f40b328a278be29a84b271be84b43bb52d8bf23d

Observation c044677d-4295-4b94-936d-514674742946 · outbound

This paper cites Reinforcement Learning and Dynamic Programming Using Function Approximators.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Reinforcement Learning and Dynamic Programming Using Function Approximators

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.500116Z

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=2026-08-14T13:42:46.153963Z digest=sha256:2460479a7ad8fd6922481584d687f3fa2b2acd7a1d231d1e57bb666452f2109a

Observation 38387a55-f649-44cb-b148-3cd75afea5c5 · outbound

This paper cites an unresolved cited work.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-14T13:42:46.158298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:42:46.158298Z digest=sha256:18e086a2cf0990d1ff96a05329bd333876245d539211906f1894cd3df769d4b5

Observation 18565ce6-2aeb-48bc-89e1-0c7b972ef5d1 · outbound

This paper cites Sutton, David A.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Sutton, David A

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.479855Z

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=2026-08-14T13:42:46.162662Z digest=sha256:0c384e17e0dc33cb9bfaad22e19a15d3231a7ec584c780a15f69254fbfdef681

Observation a39064e8-b6d7-4928-b4e0-4c18027758a3 · outbound

This paper cites an unresolved cited work.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:42:46.467555Z

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=2026-08-14T13:42:46.166443Z digest=sha256:bbf53ccef2a59f6b152274a30890ce55946ef00ef95f0387a7994c5cd92e140a

Observation f869ce81-7077-4e59-afbb-1e32c262aa19 · outbound

This paper cites Riedmiller.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Riedmiller

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.455875Z

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=2026-08-14T13:42:46.171019Z digest=sha256:62867cc01b1822a611a50dad7f606dbb95ceaccb3f59e65c9a7676064c2ffc8c

Observation 866a8033-9635-4e5d-be76-3d3867f939cf · outbound

This paper cites Multi-agent sys- tems by incremental gradient reinforcement learning.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Multi-agent sys- tems by incremental gradient reinforcement learning

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.443138Z

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=2026-08-14T13:42:46.174784Z digest=sha256:f0887dd3c7f933155605ca2e9995ece13f095fb20c439d24f4096ab0d657d489

Observation 2cb127e6-adf7-4385-94ae-267bec94bbc4 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Playing Atari with Deep Reinforcement Learning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-14T13:42:46.178756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:42:46.178756Z digest=sha256:fbecd6dc3bae760f32bda836720c87cdbfb630701fe342e615083c4bb0090a1e

Observation 08f6b8c8-0db3-4cf5-b2db-ef289ee903f8 · outbound

This paper cites Lillicrap, Jonathan J.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Lillicrap, Jonathan J

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.428964Z

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=2026-08-14T13:42:46.183173Z digest=sha256:2b8b2823021cc7997425377671455226088cea2d0127c51ccf7d3e7af8857e43

Observation 77a671df-d574-42da-acc8-0da3f11eac35 · outbound

This paper cites Carlos Garcia-Monco, Elena Astigarraga, Ainara Gonzalez, and Jordan Grafman.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Carlos Garcia-Monco, Elena Astigarraga, Ainara Gonzalez, and Jordan Grafman

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.416072Z

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=2026-08-14T13:42:46.186918Z digest=sha256:ebe6f8e0a1c57b5a35c16ebe514be71b2928f10d7007aa3a765588c0f84b5101

Observation c94113be-6588-4395-a970-8d932bb666f8 · outbound

This paper cites an unresolved cited work.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:42:46.402425Z

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=2026-08-14T13:42:46.191060Z digest=sha256:bef62358c3fa1b7157ccf406a3e48cd6ff32f0d6c499b4a7284808322e71eb9e

Observation 7a592191-4895-4e07-9653-3345cd79495f · outbound

This paper cites A softmin-based neural model for causal reason- ing.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking A softmin-based neural model for causal reason- ing

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.391194Z

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=2026-08-14T13:42:46.195975Z digest=sha256:1aca298ed1e9b450165f5ae0a20c6bd00a00c810bc53bcdf89a07020db899304

Observation 2f97b108-3462-4268-b618-7076a84ce547 · outbound

This paper cites Kingma and Jimmy Ba.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Kingma and Jimmy Ba

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-14T13:42:46.199655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:42:46.199655Z digest=sha256:32e2deee98d09d02b32a6d51055c97dc2002f592ad697fe06f62d1bf6a2efe1b

Observation d9c3d5bc-d632-482e-8e23-541e7b44e4e7 · outbound

This paper cites Stewart, and Jimeng Sun.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Stewart, and Jimeng Sun

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.370342Z

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=2026-08-14T13:42:46.203564Z digest=sha256:729822ff14a6856d92386338e1c84a13fb683a223a1ede916781e6997baaa5b2

Observation 6236c071-5416-4035-8443-5526c41ba023 · outbound

This paper cites Cooperative multi-agent control using deep reinforcement learning.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Cooperative multi-agent control using deep reinforcement learning

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.358980Z

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=2026-08-14T13:42:46.208200Z digest=sha256:1ae453699988c3686ce9cbf5fbeba53802dc038f1b8a24d89d11f384c77ad897

Observation f21a3529-4c2f-41fa-8f6c-339389ca3b12 · outbound

This paper cites an unresolved cited work.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:42:46.346719Z

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=2026-08-14T13:42:46.212578Z digest=sha256:0aaa7f5bd5414bc4e02ef49a493b2e0a41668cb472daed45952f84574f5322dd

Observation 55298849-d929-4f11-81ee-a652f369ab19 · outbound

This paper cites Causal inference in statistics: An overview.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Causal inference in statistics: An overview

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.335663Z

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=2026-08-14T13:42:46.217238Z digest=sha256:1052e00b6086bca16a7f432680404982b112bb5c3bc40799acd843054f726c6c

Observation 722d6eeb-fca0-4456-8d74-21ba7dac79cc · outbound

This paper cites Causal inference based on counterfactuals.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Causal inference based on counterfactuals

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.324920Z

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=2026-08-14T13:42:46.221077Z digest=sha256:a196976764ffc9e2d0869aa352d39f9f2c1dc08f1c8c6b7134969bc75213d081

Observation 6299355d-f805-4d32-adda-feff392c1364 · outbound

This paper cites an unresolved cited work.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 33

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:42:46.313644Z

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=2026-08-14T13:42:46.224917Z digest=sha256:278697a93a0b274f80209a62a0e0c9553cea70e4ef22699c86b381dbad38709a

Observation 76ac22de-a8df-42fb-b01b-0288f874fac2 · outbound

This paper cites Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-14T13:42:46.228900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:42:46.228900Z digest=sha256:254769744de67e4d437b5d9c7c56142b93d9f7ef061b4f810d2b50377762c51a

Observation 13ee506f-08f8-4897-b7e9-6c960041cc10 · outbound

This paper cites WOLPERT and KAGAN TUMER.Optimal Payoff Functions for Members of Collectives , pages 355–369.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking WOLPERT and KAGAN TUMER.Optimal Payoff Functions for Members of Collectives , pages 355–369

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:42:46.300364Z

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=2026-08-14T13:42:46.233335Z digest=sha256:8f510adb963cdf00c6a5de6224e4ae849bfbb08b4320b50c5511c853964b94a6

Pith citing papers

No inbound Pith citation observations are available.