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Paper Citation Record · LEDGER

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2505.19717.

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

pith.paper-citation-record.v1
2505.19717 v2

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:13:13.797334Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:42:36.301802Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

48 of 48 outbound references displayed

  • verified exact1
  • verified fuzzy38
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e5d39efb-a081-4752-b35c-9481816f62e2 · outbound

This paper cites Implicit behavioral cloning,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Implicit behavioral cloning,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-07T14:13:22.614774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1a6cdce9-e039-4a68-a949-71757b0f889a · outbound

This paper cites Diffusion policy: Visuomotor policy learning via action diffusion,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Diffusion policy: Visuomotor policy learning via action diffusion,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-07T14:13:22.402120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 545533ad-a22b-4268-b677-3107de5ee5dd · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 3

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unresolved
no resolver link, observed 2026-08-07T14:13:10.424065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:10.424065Z digest=sha256:cc77e24748e3f6e750fc290734a91909237d3b0ff4e5e22e42200a45e3f89398

Observation 2c4a7aec-3d89-47ae-9f2b-90f4d5b8d11b · outbound

This paper cites Goal-conditioned imitation learning,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Goal-conditioned imitation learning,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T14:13:22.027716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:10.458646Z digest=sha256:1149da2edd7293f63cde63123baaa8306521736d42e9bd93cad71a79616374ea

Observation 731f510a-c990-4e97-8bbe-2825ae134f8d · outbound

This paper cites Goal-conditioned imitation learning using score-based diffusion policies,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Goal-conditioned imitation learning using score-based diffusion policies,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:21.830239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:10.517972Z digest=sha256:56bfe7f04676a21d613a96c68a1551d3667de102f90beda41278a75a885af30d

Observation 9b456f13-4791-4eee-bcf3-7444acd4476c · outbound

This paper cites From play to policy: Conditional behavior generation from uncurated robot data,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning From play to policy: Conditional behavior generation from uncurated robot data,

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-07T14:13:21.654084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:10.559130Z digest=sha256:8470996f20054950f9d652e621ed61b1fa6d1a6d3ce07a48c20b678719048d07

Observation a4069876-c30a-425f-8b2a-f384bb88072f · outbound

This paper cites Nomad: Goal masked diffusion policies for navigation and exploration,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Nomad: Goal masked diffusion policies for navigation and exploration,

Reference 7

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raw_fallback, observed 2026-08-07T14:13:21.488868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:10.615836Z digest=sha256:6447184ea665a5f9ad441d4a0a13345bfa9f547065994495b6c6f646c21315a4

Observation df922980-78c7-4ef6-ac36-7b18b4a68d66 · outbound

This paper cites Multimodal diffusion transformer: Learning versatile behavior from multimodal goals,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Multimodal diffusion transformer: Learning versatile behavior from multimodal goals,

Reference 8

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raw_fallback, observed 2026-08-07T14:13:21.261925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:10.685703Z digest=sha256:810c9d7bb2b29af3fb69c3b3864e4fc78ffb8cdd209cb6b042ae9fdd89045592

Observation 95232859-c92e-44fc-a6b5-9d286f34d531 · outbound

This paper cites Ai robots and humanoid ai: Review, perspectives and directions,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Ai robots and humanoid ai: Review, perspectives and directions,

Reference 9

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verified exact
raw_fallback, observed 2026-08-07T14:13:14.277435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:10.758839Z digest=sha256:65c667a165baf022817fbf8af03b257924542cfea28229f877a5c8dadb210619

Observation bed0a074-b8f6-4ae5-8dca-5fbbc952a21b · outbound

This paper cites Advancements in humanoid robots: A comprehensive review and future prospects,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Advancements in humanoid robots: A comprehensive review and future prospects,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-07T14:13:21.075008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:10.812119Z digest=sha256:0fc6e573cae3192a9723727a3a94a16bf429346710d7bbee615b58faa1e671be

Observation 4903d5d4-4924-4edc-9666-beb5d5bda6ec · outbound

This paper cites Learning latent plans from play,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Learning latent plans from play,

Reference 11

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raw_fallback, observed 2026-08-07T14:13:20.890454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:10.903727Z digest=sha256:6d50dcc0268618dbb19e05638afd176227b8149e80345a5ed4b85b222de7bcf4

Observation fb6ed1a5-795b-4f13-93c0-28d0132aa7e6 · outbound

This paper cites Calvin: A benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Calvin: A benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks,

Reference 12

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raw_fallback, observed 2026-08-07T14:13:20.704051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:11.007525Z digest=sha256:ebe981ee6c800c656fff040a832582f7b8caf905605c07b8eda446e767d574be

Observation bdbb5133-b17e-40f3-bf55-c3befb7d3cd4 · outbound

This paper cites Mimicplay: Long-horizon imitation learning by watching human play,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Mimicplay: Long-horizon imitation learning by watching human play,

Reference 13

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raw_fallback, observed 2026-08-07T14:13:20.491154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:11.245005Z digest=sha256:c16441ccdb342195d4f7901dc5f7a79d7e61f98e097529d7aa6c05c1c42d2718

Observation 021dbde6-fc11-423c-a7f9-7defa8cfbc22 · outbound

This paper cites Is conditional generative modeling all you need for decision-making?.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Is conditional generative modeling all you need for decision-making?

Reference 14

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raw_fallback, observed 2026-08-07T14:13:20.295710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:11.604137Z digest=sha256:80eab5e40f04cdbac445de117e3874c45c211b71eaeced6ae25078b08031cb28

Observation f15a7ee0-fe1c-4b0f-a0e8-b8a78106587a · outbound

This paper cites Offline reinforcement learning with implicit q-learning,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Offline reinforcement learning with implicit q-learning,

Reference 15

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raw_fallback, observed 2026-08-07T14:13:20.106721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:11.851151Z digest=sha256:8edef15fe24704495070c75ecfe2f1a6dbd74ea18275d676942ba7d2c0c85c40

Observation 708a9874-fd61-4b2a-9b31-57e6197c721c · outbound

This paper cites Enhancing Decision Transformer with Diffusion-Based Trajectory Branch Generation.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Enhancing Decision Transformer with Diffusion-Based Trajectory Branch Generation

Reference 16

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no resolver link, observed 2026-08-07T14:13:11.951580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:11.951580Z digest=sha256:78b38b1ab8697126dac4acf97d47035ee6d8b6f96744555d121828a8e9bf508b

Observation 7443e3d9-cd8e-4f5c-9272-bc9676f77238 · outbound

This paper cites Hiql: Offline goal-conditioned rl with latent states as actions,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Hiql: Offline goal-conditioned rl with latent states as actions,

Reference 17

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raw_fallback, observed 2026-08-07T14:13:19.887373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:12.051762Z digest=sha256:8b496bc36ed620c24dcf55be306083b855aafbf06bd40aed14eebffb6bdfdbfe

Observation 4bae52af-8a73-4158-bdc7-f6b3dfb4de4a · outbound

This paper cites Stitching sub-trajectories with conditional diffusion model for goal-conditioned offline rl,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Stitching sub-trajectories with conditional diffusion model for goal-conditioned offline rl,

Reference 18

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raw_fallback, observed 2026-08-07T14:13:19.724139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:12.156465Z digest=sha256:35c52aff4d6b8445c1bb2707395dbbc3fe4ae309c6af4eeadbf13393fd2f5ddd

Observation 8a6a99a4-a041-4f00-a893-3b1fb963cc1f · outbound

This paper cites What makes a good diffusion planner for decision making?.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning What makes a good diffusion planner for decision making?

Reference 19

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raw_fallback, observed 2026-08-07T14:13:19.547599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:12.266764Z digest=sha256:d77238890c8281e592611404d3a41362fcc84fe1de61dae67d12f527ee9d2eba

Observation 3198f40b-b5fb-47f6-9ac6-8735306c7c98 · outbound

This paper cites Denoising diffusion probabilistic models,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Denoising diffusion probabilistic models,

Reference 20

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raw_fallback, observed 2026-08-07T14:13:19.350494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:12.347879Z digest=sha256:aa7ce054cf7636a3cf5403f4f19f798f3a9b12da2da1731d8e9690c4b0dab92c

Observation de914c0c-c73c-4958-a4e7-002d8378602f · outbound

This paper cites Denoising diffusion implicit models,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Denoising diffusion implicit models,

Reference 21

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no resolver link, observed 2026-08-07T14:13:12.411901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:12.411901Z digest=sha256:76cb3685e4f6fbee23b971e8e693fa74d38b5ac6bd8f87c51bd8e4883196c7aa

Observation 1306ac9a-0419-4f3a-a203-b9f51252a0f8 · outbound

This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Flow straight and fast: Learning to generate and transfer data with rectified flow,

Reference 22

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raw_fallback, observed 2026-08-07T14:13:19.113131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation fe276f90-0e4b-4eca-9a79-184924bb178e · outbound

This paper cites Planning with diffusion for flexible behavior synthesis,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Planning with diffusion for flexible behavior synthesis,

Reference 23

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raw_fallback, observed 2026-08-07T14:13:18.860586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:12.597041Z digest=sha256:1a231b9480372f6573716bb1b09bdb5111b08d57d619c99505d9cc81a5adef0e

Observation 1927f3b7-3165-40da-8259-27fc69aa2cd5 · outbound

This paper cites Generative skill chaining: Long-horizon skill planning with diffusion models,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Generative skill chaining: Long-horizon skill planning with diffusion models,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-07T14:13:18.670948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:12.675680Z digest=sha256:fa7f540937effb7920ec75157cc14f2f8250199eb224d07d8ca512980c149fb6

Observation 32d62a88-606e-466e-a467-a2a6964ed055 · outbound

This paper cites Simple hierarchical planning with diffusion,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Simple hierarchical planning with diffusion,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-07T14:13:18.441594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:12.741001Z digest=sha256:516ca2a20dd392a64c3294aa0888d6f782dbbf6abb8da97d17aa1059ca6f4fa0

Observation 834b33c4-2866-4984-9b55-7fba85d288e0 · outbound

This paper cites Generative Trajectory Stitching through Diffusion Composition.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Generative Trajectory Stitching through Diffusion Composition

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:12.795022Z digest=sha256:a8f82dd83325ba376cc2ece70b73df23a728bd0c30e9a8f1b5700b3b44493454

Observation 7a21a3ae-a52f-4449-9a5f-04e6ed277102 · outbound

This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:12.862097Z digest=sha256:df9304ca23626ed09cb988c4c1d077d05bfb3649f3ac15fada56e0083df883d2

Observation 70781da1-cd8b-409c-8c14-15bebfdf3d53 · outbound

This paper cites Building normalizing flows with stochastic interpolants,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Building normalizing flows with stochastic interpolants,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-07T14:13:18.235006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:12.907981Z digest=sha256:c461cc1d8709ef520739c4378b5509d8f83e199abc6c2e0ea14ffa680a437cea

Observation 89c0b14b-1dcb-463d-82d1-5d5875188898 · outbound

This paper cites Flow matching imitation learning for multi-support manipulation,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Flow matching imitation learning for multi-support manipulation,

Reference 29

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raw_fallback, observed 2026-08-07T14:13:17.950601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:12.941740Z digest=sha256:653a093484da2e3897d9e8559a3f5d77a55ab4e43b5fb301fea221524e7947bb

Observation c853b701-481d-4bce-8cd9-f0996d581477 · outbound

This paper cites Adaflow: Imitation learning with variance-adaptive flow-based policies,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Adaflow: Imitation learning with variance-adaptive flow-based policies,

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-07T14:13:17.636475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:12.981582Z digest=sha256:c457d16c50b504d1383f9cbdcfd484f0cf46580e1b32627f38e871820b1cabbe

Observation 96ea8430-2587-4a30-bb67-39060cfb86a5 · outbound

This paper cites Riemannian flow matching policy for robot motion learning,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Riemannian flow matching policy for robot motion learning,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-07T14:13:17.342071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.016061Z digest=sha256:a28e05b21fe574d3949dd4b39dea4f7f6e88d433a68254c4f9b9601c011b13e0

Observation ef7e17d1-7ff4-4255-a85d-8a98bc72d3c3 · outbound

This paper cites Flowpolicy: Enabling fast and robust 3d flow-based policy via consistency flow matching for robot manipulation,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Flowpolicy: Enabling fast and robust 3d flow-based policy via consistency flow matching for robot manipulation,

Reference 32

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raw_fallback, observed 2026-08-07T14:13:17.058813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.064149Z digest=sha256:5fbe2a355e23dd4137dc6afdf3b3d27496d0fb32fe794834774185782e6429c0

Observation 8205e69e-8374-4dde-aea1-9753110244a2 · outbound

This paper cites Energy-Weighted Flow Matching for Offline Reinforcement Learning.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Energy-Weighted Flow Matching for Offline Reinforcement Learning

Reference 33

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no resolver link, observed 2026-08-07T14:13:13.112158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:13.112158Z digest=sha256:ef3c7b95de01e98c36bbbaa2975c305e722b105efc822f2c1f828ebf5a14978a

Observation fa4a88f4-afdb-4f5d-98f1-c7b338a2f3e2 · outbound

This paper cites Flow Q-Learning.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Flow Q-Learning

Reference 34

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no resolver link, observed 2026-08-07T14:13:13.146702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:13.146702Z digest=sha256:b5ac46ac98db1284d1c05f214bda2a934ddcd87fc3d68d07af81b4b564406b4a

Observation 01f4e5b4-624c-4376-9fe7-d79390b9d59e · outbound

This paper cites Hindsight experience replay,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Hindsight experience replay,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:16.801712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.205702Z digest=sha256:f99e3a46e2b90382ad0d1156586425e32bf87f2523f6c1e3f327b811c886702f

Observation 1f78d3f2-69d4-4616-a575-2b91b380fc2c · outbound

This paper cites Asymmetric least squares estimation and testing,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Asymmetric least squares estimation and testing,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:16.509655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.280275Z digest=sha256:6735d1e722925140ca710a9852727d99e579546e1f820c8ebe4f5c857667b620

Observation ec3fd0cf-ccde-487c-b2c0-01cff93c2db5 · outbound

This paper cites Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:13:13.314904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:13.314904Z digest=sha256:8dfd28f3804d0af88a81d7fa9adf43d1a09b96ae266a982efee0f2dcf2588cbc

Observation 19850cc5-4ade-4f1a-87b4-16ffda805e30 · outbound

This paper cites Learning from reward-free offline data: A case for planning with latent dynamics models,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Learning from reward-free offline data: A case for planning with latent dynamics models,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:13:13.343958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:13:13.343958Z digest=sha256:1b89a9fd3b0b73d46610c92dbb7a6b99e5824b4e60bf92c91267af17897538e9

Observation 8eb96060-8aa9-4b17-ab64-bf9d1822dbca · outbound

This paper cites Double q-learning,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Double q-learning,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:16.263908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.389500Z digest=sha256:59eabe8a0b86e68f3d8ecf117b50ff2af63584dcffcad147bb777a265fdc462a

Observation 663eabc0-78d3-47f2-902d-36d325c33f32 · outbound

This paper cites Ogbench: Benchmarking offline goal-conditioned rl,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Ogbench: Benchmarking offline goal-conditioned rl,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:16.015627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.423507Z digest=sha256:dddbd480345e70895b89ca181c426bcd215ad6b72aca6a2aa8857fdd3f680e03

Observation 4626e549-5c9e-4d85-b8ac-0e43bf6fcc8c · outbound

This paper cites Learning to reach goals via iterated supervised learning,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Learning to reach goals via iterated supervised learning,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:15.786014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.501243Z digest=sha256:7b0ed7c4592a3bfccc3e8764c0d3f7c5386a065a61fb31bd08b0016ff778ff91

Observation a013d2db-8ba5-4a23-b30c-3a3a2d508bcd · outbound

This paper cites Optimal goal-reaching reinforcement learning via quasimetric learning,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Optimal goal-reaching reinforcement learning via quasimetric learning,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:15.541101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.559490Z digest=sha256:ca77c72fc1f29fa8ba6d3451dbdc275e2a7b2650d631fb7b88f86be9fe7c579d

Observation 4bb78712-a42b-4ab0-adb2-5b63d0bd26d3 · outbound

This paper cites Contrastive learning as goal-conditioned reinforcement learning,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Contrastive learning as goal-conditioned reinforcement learning,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:15.354411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.603159Z digest=sha256:d12f9db28b70b9cd456cf859cf676386626d2c968cfcfe78424da4ebbac81da1

Observation da8add89-25ef-46c2-b455-fe45eb9974f8 · outbound

This paper cites Multi-contact whole-body force control for position-controlled robots,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Multi-contact whole-body force control for position-controlled robots,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:15.185382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.645522Z digest=sha256:123ac114fcaac2e638412d5c32a0995c326308b0877b057ae32db91a311e61a6

Observation 762971fe-d9bf-44db-bbe8-893477d1d338 · outbound

This paper cites Multicontact motion retarget- ing using whole-body optimization of full kinematics and sequential force equilibrium,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Multicontact motion retarget- ing using whole-body optimization of full kinematics and sequential force equilibrium,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:15.007210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.675206Z digest=sha256:ba4e454f7fb59ae3ad2bf337274b10beded8c9ff3a29e701fcfe6dcf72421d5c

Observation 0f028772-3bba-49c6-b87b-8fecd00b2bc4 · outbound

This paper cites Collaborative bimanual manipulation using optimal motion adaptation and interaction control,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Collaborative bimanual manipulation using optimal motion adaptation and interaction control,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:14.893102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.734489Z digest=sha256:d203916037905863d83973074092838ba26a225b0c0432fcfe1db3c30ad45bc7

Observation ee689ab7-eded-40f9-a5a4-e323512eafca · outbound

This paper cites Impala: Scalable distributed deep-rl with importance weighted actor-learner architectures,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Impala: Scalable distributed deep-rl with importance weighted actor-learner architectures,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:14.724425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.790169Z digest=sha256:7ba950c27d24b2f9ccf6ca3794ccd38412f7b633e7ec6531a02e88154089fab9

Observation ee2d83bd-d09c-4c3d-8058-2bd59ce1f32b · outbound

This paper cites On the continuity of rotation representations in neural networks,.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning On the continuity of rotation representations in neural networks,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:13:14.515702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:13:13.797334Z digest=sha256:538f90f70d05ecfe14ae7b12bd4c486b7bdc9d23b17216c10a16033ee260c169

Pith citing papers

Observation b662e099-3a64-48af-be54-918eed490f37 · inbound

Native Extrapolation Awareness in Flow-Based Conditional Generation cites this paper.

Native Extrapolation Awareness in Flow-Based Conditional Generation Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-02T23:42:36.301802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:42:36.301802Z digest=sha256:342f68c39d8b4206bbcd8b6515cbb830477754665cf879eb96bacdc0b14ad34c