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Paper Citation Record · LEDGER

GenPlan: Generative Sequence Models as Adaptive Planners

As of 13 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2412.08565.

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

pith.paper-citation-record.v1
2412.08565 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:51:01.284638Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

33 of 33 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved32
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6cddaacd-779c-4905-8edf-5d6a90f0d760 · outbound

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

GenPlan: Generative Sequence Models as Adaptive Planners , " * write output.state after.block = add.period write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.105277Z digest=sha256:29e79111a2a182f5538ed511c275963b21f833be799a45587e0c1e5f1a2c33e9

Observation 984e48e5-e91e-4e31-a13a-d225adf08445 · outbound

This paper cites write newline.

GenPlan: Generative Sequence Models as Adaptive Planners write newline

Reference 2

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source=arxiv_source observed=2026-08-11T17:51:01.111316Z digest=sha256:de8b890f776555fd7cf4a80bbd68dff6f303ca040b845f079e578959596b978f

Observation d9423a47-8dad-4945-87ed-21d0fc78fd6a · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T17:51:01.117675Z digest=sha256:959306363ba2defb9210055885b744ce81ed4d33b9c9f3a86dcc81da3758121d

Observation 030912b2-97ef-4b1a-8afe-b47c236c8ec8 · outbound

This paper cites Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design.

GenPlan: Generative Sequence Models as Adaptive Planners Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design

Reference 4

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source=arxiv_source observed=2026-08-11T17:51:01.125389Z digest=sha256:ad56db6e18b5ee1bf22f53719d3c65b27f841bcee9235580b08770f724c66b4d

Observation c09106f6-fdfe-4ae6-83f7-0b137e41d94b · outbound

This paper cites B.; and Vela, P.

GenPlan: Generative Sequence Models as Adaptive Planners B.; and Vela, P

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-11T17:51:01.817821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T17:51:01.131335Z digest=sha256:51798971426599cad8df491ad2b74ea0a195555deb43d64bb9249336de861515

Observation 59ba18a2-8b6d-48bd-a208-e809a2962796 · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T17:51:01.136641Z digest=sha256:64a449aa4d94f8bb3e2e50f87db891084c5aa5122868b9dbf9da3466fddc7c19

Observation 5864aba3-2e64-470d-b065-7aa2c6ac02f3 · outbound

This paper cites H.; and Bengio, Y.

GenPlan: Generative Sequence Models as Adaptive Planners H.; and Bengio, Y

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.141926Z digest=sha256:408d7fdf3b1e56524487dee3fe7164d734dea6ba5d353736696460c3612f5bbf

Observation 335bddcd-16c8-4adb-aa25-3dd1eea70858 · outbound

This paper cites Diffusion Policy: Visuomotor Policy Learning via Action Diffusion.

GenPlan: Generative Sequence Models as Adaptive Planners Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.146929Z digest=sha256:468b852523f4a00d4e75f39b1cb70e68fcdce84275de7cdb42aa0913922c80fa

Observation 313833ea-707b-46f7-8395-3935da4aefac · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

GenPlan: Generative Sequence Models as Adaptive Planners BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.152902Z digest=sha256:0a59f60e9cfdadcb468ee220a41e4573d31da0cf1e28e67a7cbd27b5d2a1abca

Observation 60191ffa-75ce-4cf9-ae2b-e11319fbfa75 · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T17:51:01.157867Z digest=sha256:8037a1c893e1997cfa389106762df1edd32240577c0cd9b5494c36afbcc4d12d

Observation d759b893-d01a-4ad0-bbcf-d9e136c48534 · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 11

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T17:51:01.162821Z digest=sha256:af769c29d6e9472b5ffdcb2bce8e4ad4b567192598d08c815e6cb363870d63ab

Observation c27cb086-97ec-4c46-938a-56b9e3548657 · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 12

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raw_fallback, observed 2026-08-11T17:51:01.737796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 6a7c0059-a4d2-48df-ae67-21c73453a45e · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 13

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raw_fallback, observed 2026-08-11T17:51:01.720415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T17:51:01.173962Z digest=sha256:832ec29f064de584e7253da50975ba393e22c5a52b9ba4937d45044417343ec6

Observation cb819eda-54b3-42ee-8521-12ea4848d58c · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 14

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no resolver link, observed 2026-08-11T17:51:01.179272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.179272Z digest=sha256:10a7abc0dd8f8b9501a454b3a46782cf368a9a9ad75e8e18cd06724b4600da6d

Observation ac9b9cec-f2f6-4f4a-87ac-538c553396b1 · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T17:51:01.184099Z digest=sha256:facdc6518419ab2a2a15a008e5a6d572449fd8a42eeb1e4cd8701ebb9d0f4a89

Observation 59ad7f52-848d-400c-87bc-a75173319e6d · outbound

This paper cites Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis--Hastings.

GenPlan: Generative Sequence Models as Adaptive Planners Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis--Hastings

Reference 16

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no resolver link, observed 2026-08-11T17:51:01.189310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.189310Z digest=sha256:b520a7c797b635edf8e0f3ad77e459dbc9e6de1f216f212d461b264ec4aeeb6c

Observation 5420df7a-9483-4c9b-85bf-775f86375ff4 · outbound

This paper cites Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning.

GenPlan: Generative Sequence Models as Adaptive Planners Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning

Reference 17

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no resolver link, observed 2026-08-11T17:51:01.195551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.195551Z digest=sha256:fa70cea6d7a08d95c86d7f10faabb397b2dc6a74a7aabd1aa3885bf6906802c7

Observation 20f7e92c-744a-41dc-ad7b-e5d5e28a1895 · outbound

This paper cites Reinforcement Learning with Deep Energy-Based Policies.

GenPlan: Generative Sequence Models as Adaptive Planners Reinforcement Learning with Deep Energy-Based Policies

Reference 18

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no resolver link, observed 2026-08-11T17:51:01.200728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.200728Z digest=sha256:f1a2dcf9d56b3b8c16ba9e83d4e31769da3807396774e5a0df0a487ce68d54cf

Observation c94faeb0-bdf0-48b7-bfcc-b05ec0dc0e19 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

GenPlan: Generative Sequence Models as Adaptive Planners Denoising Diffusion Probabilistic Models

Reference 19

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no resolver link, observed 2026-08-11T17:51:01.207301Z

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source=arxiv_source observed=2026-08-11T17:51:01.207301Z digest=sha256:8cb99d52ed58ae1792fd2df9efc307dde4b4b9f739dfa3f56b5333e21b8d25f0

Observation 84b01d54-6785-4e8f-a983-9791c2b3b2d9 · outbound

This paper cites Planning with Diffusion for Flexible Behavior Synthesis.

GenPlan: Generative Sequence Models as Adaptive Planners Planning with Diffusion for Flexible Behavior Synthesis

Reference 20

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no resolver link, observed 2026-08-11T17:51:01.214329Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.214329Z digest=sha256:811c0bfeaf6dac60beb5e5a2f10b449d0b46b4c5fb4234926a3cdc552540abcc

Observation df8c7c42-968e-4e02-97ef-555344d3859d · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 21

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raw_fallback, observed 2026-08-11T17:51:01.670860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 00097875-f3b3-4a9b-85ae-96597a627ad1 · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

GenPlan: Generative Sequence Models as Adaptive Planners Offline Reinforcement Learning with Implicit Q-Learning

Reference 22

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no resolver link, observed 2026-08-11T17:51:01.226545Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.226545Z digest=sha256:af1211f8e4b617c149c16109908c095c78ba1b3ea13c852d4246ee10cb6ecc89

Observation 5e064230-2c65-44ed-93e4-2c105f375e70 · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 23

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raw_fallback, observed 2026-08-11T17:51:01.652507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T17:51:01.231643Z digest=sha256:2035c9aa1bca563d16dfdc29381190a290c1861405306beccc13ec64a8e6b618

Observation 5e8d5b20-5332-441f-ae3d-5214a563ee5f · outbound

This paper cites Investigating Compounding Prediction Errors in Learned Dynamics Models.

GenPlan: Generative Sequence Models as Adaptive Planners Investigating Compounding Prediction Errors in Learned Dynamics Models

Reference 24

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.236890Z digest=sha256:0f4ba1125ecb02c51c3aa9865539790a0020e32c3c83e0e780677d4194d30157

Observation 0fba7ff2-aa82-4f8b-9a00-91d5c707ca0c · outbound

This paper cites Behavior Generation with Latent Actions.

GenPlan: Generative Sequence Models as Adaptive Planners Behavior Generation with Latent Actions

Reference 25

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no resolver link, observed 2026-08-11T17:51:01.242418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.242418Z digest=sha256:139ba97aba728669724fa3cd92b9582ab9a7a1db4997d59e3dd5b6ec92aa8a11

Observation 7318cd86-8702-4fe8-8d3f-c64c0c17e69a · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

GenPlan: Generative Sequence Models as Adaptive Planners Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 26

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unresolved
no resolver link, observed 2026-08-11T17:51:01.247534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.247534Z digest=sha256:61398376c08c34f49df15fd8d909386b48147bd68e78d5849288e632c0e6fe81

Observation 8348593a-04b3-42b6-9d2e-cf91a489c6b1 · outbound

This paper cites Offline Pre-trained Multi-Agent Decision Transformer: One Big Sequence Model Tackles All SMAC Tasks.

GenPlan: Generative Sequence Models as Adaptive Planners Offline Pre-trained Multi-Agent Decision Transformer: One Big Sequence Model Tackles All SMAC Tasks

Reference 27

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no resolver link, observed 2026-08-11T17:51:01.252978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.252978Z digest=sha256:a8e14c5dd0c39b37e7aaacb99035ce90403a073d2294538f9647d20c3fcf4a37

Observation 5d939f4a-dd7b-4f27-b190-5be118226f89 · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 28

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raw_fallback, observed 2026-08-11T17:51:01.636393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T17:51:01.258443Z digest=sha256:81912e221fbc5d025c0e0af6ab3636f908637aba4903d5b95f506fb2723ff311

Observation 697d7ca2-eb1d-4c4d-a695-be48221c09c2 · outbound

This paper cites Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions.

GenPlan: Generative Sequence Models as Adaptive Planners Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions

Reference 29

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no resolver link, observed 2026-08-11T17:51:01.263833Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.263833Z digest=sha256:ac30bef5e4724102689f9582ee5ae7243bfa9a1c26a76bc61335c47b25f29b33

Observation dfb71f17-22cb-491d-86e9-82424a35efab · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 30

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unresolved
raw_fallback, observed 2026-08-11T17:51:01.619816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-11T17:51:01.269209Z digest=sha256:8c084d5e91c64d78886dcae875d511d0e3b9d4e70b36af9fa6c5201e9486fff1

Observation be3b6b6f-218d-413d-aa5d-1bcbb7db222a · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 501acdbe-9c6e-4593-830b-559ad8c36396 · outbound

This paper cites MOPO: Model-based Offline Policy Optimization.

GenPlan: Generative Sequence Models as Adaptive Planners MOPO: Model-based Offline Policy Optimization

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:51:01.279515Z digest=sha256:9eddd72a9e504ab0ab81df666a617feeeacc7e64dc6957f00343a3703684f22f

Observation f5b2742c-452f-47fd-ba74-759bbb6244ed · outbound

This paper cites an unresolved cited work.

GenPlan: Generative Sequence Models as Adaptive Planners Unresolved cited work

Reference 33

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raw_fallback, observed 2026-08-11T17:51:01.586965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Pith citing papers

No inbound Pith citation observations are available.