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Paper Citation Record · LEDGER

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization

As of 15 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2412.07639.

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

pith.paper-citation-record.v1
2412.07639 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:46:17.581638Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

34 of 34 outbound references displayed

  • verified exact2
  • verified fuzzy6
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2585beef-4765-44c5-b92d-c74fb8ae052d · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization , " * write output.state after.block = add.period write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T18:46:17.456660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:46:17.456660Z digest=sha256:4d5242847899c412fd4841500bd82e85b010b0611cc304db7a0588dc389bbe50

Observation 8bef3090-4190-436e-8014-8c19e253ac5f · outbound

This paper cites write newline.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization write newline

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-11T18:46:17.461660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:46:17.461660Z digest=sha256:047d56fffccf0c7709b93b813f37f3bb5b5f1b0513e1a129590163e0d02a2fb2

Observation 3329ad65-970f-43c4-a03e-c27d09aac75c · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.951459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.466441Z digest=sha256:2792442af0522f8aa8d2e296d4335f4958e024a5e79fdee039618067aeebc18c

Observation 70c2ee7e-8890-444e-b408-a0f0e621b83b · outbound

This paper cites Multi-Agent Coordination via Multi-Level Communication.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Multi-Agent Coordination via Multi-Level Communication

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:46:17.671709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.470709Z digest=sha256:a64cf9eed4982748f4e2cdef21a1f48d9660cde20eff52268a646c2a3914a1e0

Observation 2df5b566-0ae2-47dc-b93e-d5f663166e77 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.940922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.475746Z digest=sha256:4931ac1e2140f17d4032c134ba0807ce6d456c4fce488c617cef0317faa56722

Observation 47d95fc6-2c48-430e-8c14-a857d0f8f1f0 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.930107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.479835Z digest=sha256:26e61a0e4329196177b498c6b763b322649d6cc4e45631fe771721b573929626

Observation 3f8f3228-f4e4-450c-a40a-999db5777a26 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T18:46:17.483893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:46:17.483893Z digest=sha256:7943b4b0e0786f61a7df05e1c943091fef835347b51ac047aeab2b32246c34cc

Observation 6bffe705-1e1c-454d-902c-1e1adcda35c7 · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Soft Actor-Critic Algorithms and Applications

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T18:46:17.487995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:46:17.487995Z digest=sha256:f49851a896f124e9af60766e1c073d33e5c0858a8a622c7dbe3bac7f61ad3856

Observation 569e532e-8196-4fdb-a453-9ae511850052 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.912537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.492178Z digest=sha256:2a60351a3cf750e7f57e541eb73b3a777e55a73f9cf33747d28247291d97fb83

Observation bf11f350-3e7d-4a3d-b4a4-7474d2493e98 · outbound

This paper cites G.; Chen, R.; Wen, M.; Wen, Y.; Sun, F.; Wang, J.; and Yang, Y.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization G.; Chen, R.; Wen, M.; Wen, Y.; Sun, F.; Wang, J.; and Yang, Y

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:46:17.902691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.495763Z digest=sha256:7d3b4f0f6612725fe0b5e2a50e3ecdf581358e6bf753d057fdf1d5285e496c9e

Observation 78650811-09e7-49f2-a4aa-33148eeae3cd · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T18:46:17.499064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:46:17.499064Z digest=sha256:0ad3855fb03a2fd2bf1201064ccf455cff0304d197da270287358cca68bb5161

Observation fde00527-41bf-4b32-a2cf-37d97f86ebd4 · outbound

This paper cites Improving Generalization and Data Efficiency with Diffusion in Offline Multi-agent RL.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Improving Generalization and Data Efficiency with Diffusion in Offline Multi-agent RL

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:46:17.644430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.502439Z digest=sha256:8c8963d741817073e437a2df5fb642a01e08193baa8766b5286f451ba5b2d071

Observation af474bd8-27db-4185-8caa-36c13204a622 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.886510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.506247Z digest=sha256:0df9cf28e1179f665b137d102e1b761fa47a8c51f759e041bb67973f05a54b1a

Observation b9283b72-8d96-4262-b258-ffb0707464c8 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.877666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.509669Z digest=sha256:61e19bbe412f3cf8ebc010cbf62e70e80436e7e46ccaa23ea04e5ca4c8729534

Observation acccd921-64bb-4403-b00f-1a2056855d7f · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.868082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.512882Z digest=sha256:f327577dea7fc83c260613e00d9723d47341af54d2b472045049dfe5da91c789

Observation 419cc7d3-245f-4caf-b2fd-ddc5ea095370 · outbound

This paper cites E.; Lee, J.; Yoon, J.; Leonardos, S.; Abbeel, P.; and Kim, K.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization E.; Lee, J.; Yoon, J.; Leonardos, S.; Abbeel, P.; and Kim, K

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:46:17.857024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.516238Z digest=sha256:3cd4e7b210c3993f2ebe5355dbeec7efb49d64ed8d477ecef55da02b8ba6234a

Observation 142f1f8e-c43c-4232-8b4a-c5a91f2b93c9 · outbound

This paper cites D.; and Palfrey, T.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization D.; and Palfrey, T

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:46:17.846150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.519324Z digest=sha256:c2d7b0cfdf84bea102221010b038618ce6a050921811ef7ef543385d7a58b1c8

Observation a6d18b01-5914-4b7b-97c4-4c872f019b44 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.835791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.522239Z digest=sha256:dcffd4f8c43c78f62e5162c99a86e6ce7fc2be82ab735abea9ad0b55109af66c

Observation 2e412280-ffe3-4f35-9cb2-85ed5f354b29 · outbound

This paper cites S.; Farquhar, G.; Foerster, J.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization S.; Farquhar, G.; Foerster, J

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:46:17.825375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.525410Z digest=sha256:f7d68d6ecaa00ab4646c76a65850cd2d60e603d49edd5780de9e63c745919acd

Observation 4e803943-6ce8-4647-afbb-383f5c051e1c · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.813902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.528767Z digest=sha256:7fbeca351cdd18dde9d52509e1a10c71b403ca0dc904b19f3418e43154a47a2d

Observation dd9c5fe8-d921-4066-87ad-cfaa7aff26a8 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.802710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.532136Z digest=sha256:8576ba1c0ad15b855651bcf8225cbbcfefcb4b33a7ee0d870dc23ca9b004a00c

Observation 343ecda5-8128-4110-a083-f722a20287de · outbound

This paper cites J.; Hostallero, D.; and Yi, Y.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization J.; Hostallero, D.; and Yi, Y

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:46:17.791997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.535725Z digest=sha256:0a8b8aedac54714d453db5fc7a52650f72a430960455a1ee5df295efa9ba74b7

Observation f6a8cb02-ba31-413a-8e52-05ced676907e · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.780091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.538775Z digest=sha256:06e4a738e268eaba207e3de57dd1b7db8555615009b406b09d7fe33a93805d36

Observation 576032bb-89b8-4f5e-aeab-2373141c8210 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.768301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.542136Z digest=sha256:2990e77ab2f59c4c1bc618b88275940f009201c68a88222bb3c4a4d7c0c8f586

Observation ef2087b7-aefe-40d2-9566-a5d1a16a2df6 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.757357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.545752Z digest=sha256:83e2d7ca6f089d602b844e42eacdaca864f9b3cdb336b31bd09abc8a502ce447

Observation 190453a1-6e9b-4738-9d8a-bca5bc3438b0 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.746213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.550838Z digest=sha256:e4dd22f472bb220b5a7e32f5d5929b833033f0a3ccec3bdb626597a0b63384a5

Observation c1d0d3f4-8339-4c04-b38f-d8249696fb76 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.735830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.554942Z digest=sha256:b11171b6a68c196f12ee44371f5363a7e9b6c1117c492ac4e9721cabda129cd8

Observation bcc260d7-4177-49cc-98ff-78e648482a03 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.725764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.558907Z digest=sha256:b71acbd31730be1ffe06e25f3757a8b10749cc2d192d27f698cad5caf95a42e3

Observation ce0b7ee3-6478-40aa-bff1-edd48fd4168a · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.715669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.562798Z digest=sha256:bd5502535b6083ae7fd6950ee64690b211e90d96ac576d2e8ba4683fa5eae2e0

Observation a0b8b1e2-81ac-4567-aab7-0ab70e04b16f · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.704879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.566462Z digest=sha256:5e6fb646d7c24e9a694a901e8e4e07b5bd812c0c420f8b85835b7b7f473bd8bc

Observation 96b55309-edfd-446f-a81d-d4d080885d95 · outbound

This paper cites an unresolved cited work.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:46:17.692820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.570036Z digest=sha256:24d9b3fcf1be5364a156a6b4b248046aa144deef32250e97aa2dfc127d3a0ab5

Observation a01f88b0-1bf2-462f-9148-550ce3f9243c · outbound

This paper cites M.; and Wu, Y.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization M.; and Wu, Y

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:46:17.682432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T18:46:17.573647Z digest=sha256:6ae328b387681befb4dfd05d23c09a216a78f7f857c270ffe066ead0f0057f70

Observation b104da63-e063-4565-8a43-fbb44c8287df · outbound

This paper cites Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-11T18:46:17.577423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:46:17.577423Z digest=sha256:4b47122f0612e9be8e757abacfbcdc381754c524fec0f6d173f934555440e312

Observation d9aab2cb-1049-489b-a93f-1ccdfdab2402 · outbound

This paper cites MADiff: Offline Multi-agent Learning with Diffusion Models.

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization MADiff: Offline Multi-agent Learning with Diffusion Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-11T18:46:17.581638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:46:17.581638Z digest=sha256:70d089d910995ab39bdd973cda5a39521bfda90ddefdb91fc4dd5654eab7a2e2

Pith citing papers

No inbound Pith citation observations are available.