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Paper Citation Record · LEDGER

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration

As of 20 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.29482.

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

pith.paper-citation-record.v1
2607.29482 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T06:17:35.717030Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

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Outbound references

Observation 53c83782-3096-48e3-a77c-29b9cba7045c · outbound

This paper cites A survey of robot learning from demonstration,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration A survey of robot learning from demonstration,

Reference 1

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Observation 288c908e-266d-46bf-8540-946be21adc7a · outbound

This paper cites Generalizable task representation learning from human demonstration videos: A geometric approach,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Generalizable task representation learning from human demonstration videos: A geometric approach,

Reference 2

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source=pdf_text observed=2026-08-03T06:17:35.582341Z digest=sha256:e6e814fa8b42f483e708a88ced97b7918f77b93c3468ed8bb78c9457877f98bf

Observation 081409e4-2270-4a9d-b821-c62081d5bc46 · outbound

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

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Diffusion policy: Visuomotor policy learning via action diffusion,

Reference 3

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Observation 6bdae678-ca02-4ba3-9f5b-254e1d6f5e42 · outbound

This paper cites Flow Matching for Generative Modeling,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Flow Matching for Generative Modeling,

Reference 4

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source=pdf_text observed=2026-08-03T06:17:35.591929Z digest=sha256:6bb201fc3a6d198a2fa60765ed1f6532a614e91a885ad8537486084b39b921bd

Observation 78c51f92-ecc7-46c2-a652-3b59c58f59c1 · outbound

This paper cites Denoising Diffusion Probabilistic Models,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Denoising Diffusion Probabilistic Models,

Reference 5

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source=pdf_text observed=2026-08-03T06:17:35.596738Z digest=sha256:3e9a95f55b4353fc8b2a9840bea80593978e5a08dcc9cd0d6f65f9d7848b43f2

Observation b979563d-95df-42cf-a482-c25592965508 · outbound

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

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Stochastic Interpolants: A Unifying Framework for Flows and Diffusions,

Reference 6

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Observation 5ad54d9c-b7a9-4b71-8c4a-afe97fada4a7 · outbound

This paper cites Probabilistic Forecasting with Stochastic Interpolants and F ¨ollmer Processes,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Probabilistic Forecasting with Stochastic Interpolants and F ¨ollmer Processes,

Reference 7

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source=pdf_text observed=2026-08-03T06:17:35.610624Z digest=sha256:e110535e5faf058675278c826dbf67e0858e9114ac7c7699771ce181081b1bf3

Observation 512f5460-c991-477a-9d24-b2334b83e9b9 · outbound

This paper cites Goal-Conditioned Imitation Learning using Score-based Diffusion Policies.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Goal-Conditioned Imitation Learning using Score-based Diffusion Policies

Reference 8

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source=pdf_text observed=2026-08-03T06:17:35.615642Z digest=sha256:4f219474b62d270f33e4ae7d6beafc3feb5e4357ef3bbaf5ddbd1708805fe742

Observation c8dd2cea-b964-48fe-bb3b-c5059fa128b4 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow,

Reference 9

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source=pdf_text observed=2026-08-03T06:17:35.620500Z digest=sha256:d50dfe1e193405addd3f7240bc8dbb3506df099be8070ee59d604da33b510d7d

Observation d38eb670-6351-491a-a757-6c05393f7a9b · outbound

This paper cites Consistency models,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Consistency models,

Reference 10

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source=pdf_text observed=2026-08-03T06:17:35.624757Z digest=sha256:400ad1c10a75587a0c6bdf4bcb3e6d34ec65ba72ab0ac4e70afe8defef004de7

Observation 6956d4eb-6ea2-41bf-9144-a8a16192a1b4 · outbound

This paper cites ActionFlow: Equivariant, Accurate, and Efficient Policies with Spatially Symmetric Flow Matching.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration ActionFlow: Equivariant, Accurate, and Efficient Policies with Spatially Symmetric Flow Matching

Reference 11

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Observation 682defb3-4ebe-4548-a4c2-7aa20034a6af · outbound

This paper cites $π 0$: A Vision-Language-Action Flow Model for General Robot Control,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration $π 0$: A Vision-Language-Action Flow Model for General Robot Control,

Reference 12

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source=pdf_text observed=2026-08-03T06:17:35.633534Z digest=sha256:2ad286d9090c65959c6d0d1af36d123bb8c0cb50b56fdec8c8af6e155bac69af

Observation f94aca90-c023-42ef-96f6-4dea8d08cb5e · outbound

This paper cites Flow Policy: Generalizable Visuomotor Policy Learning via Flow Matching,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Flow Policy: Generalizable Visuomotor Policy Learning via Flow Matching,

Reference 13

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source=pdf_text observed=2026-08-03T06:17:35.638040Z digest=sha256:d1d139b926a741b70e606cf7bec4a8059a35aa2b608c3abd5e1334820764c989

Observation 680a69bf-5960-426e-92d4-bff8bf3f1234 · outbound

This paper cites ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training,

Reference 14

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source=pdf_text observed=2026-08-03T06:17:35.650199Z digest=sha256:97b06bff4471e8c061558fb9f27d296d68bee0080ed541a0d6a10cec302f011c

Observation 8e7b7662-bfd8-48e6-950b-00084cf0bbfc · outbound

This paper cites Multisample Flow Matching: Straightening Flows with Minibatch Couplings,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Multisample Flow Matching: Straightening Flows with Minibatch Couplings,

Reference 15

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source=pdf_text observed=2026-08-03T06:17:35.654969Z digest=sha256:afd30ff605f5565ea4d8c69bda899075031599bda616201d8d4091462aa675a1

Observation e24ef8ca-d619-4ecf-b6d6-2f073463bb42 · outbound

This paper cites Improving and generalizing flow-based generative models with minibatch optimal transport,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Improving and generalizing flow-based generative models with minibatch optimal transport,

Reference 16

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Observation af1dec0f-9575-4759-a358-7c2faa9a4610 · outbound

This paper cites Fast Flow-based Visuomotor Policies via Conditional Optimal Transport Couplings,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Fast Flow-based Visuomotor Policies via Conditional Optimal Transport Couplings,

Reference 17

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Observation 96f6d10a-8a26-423a-97a2-9a92e84705c3 · outbound

This paper cites Diffusion Schr¨odinger Bridge with Applications to Score-Based Generative Modeling,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Diffusion Schr¨odinger Bridge with Applications to Score-Based Generative Modeling,

Reference 18

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source=pdf_text observed=2026-08-03T06:17:35.668029Z digest=sha256:b051091937487d6db1bf43cb94ff54477332b7985e06ba5b0efa8b5144bb633a

Observation 90435e87-c8a7-4f61-ba26-0ab473c904ab · outbound

This paper cites Likelihood Training of Schr¨odinger Bridge using Forward-Backward SDEs Theory,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Likelihood Training of Schr¨odinger Bridge using Forward-Backward SDEs Theory,

Reference 19

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Observation c821e233-fe7d-45fd-a80a-91bab24e447d · outbound

This paper cites Simulation-Free Schr ¨odinger Bridges via Score and Flow Matching,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Simulation-Free Schr ¨odinger Bridges via Score and Flow Matching,

Reference 20

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Observation 5b9bb5b9-f662-495b-8a05-880d259491d8 · outbound

This paper cites Stochastic Interpolants with Data-Dependent Couplings,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Stochastic Interpolants with Data-Dependent Couplings,

Reference 21

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Observation 48aafeec-2184-4fc8-86ef-31f48413ac3c · outbound

This paper cites STFlow: Data-Coupled Flow Matching for Geometric Trajectory Simulation.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration STFlow: Data-Coupled Flow Matching for Geometric Trajectory Simulation

Reference 22

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Observation 4277fd1b-6d5a-45d8-9eaf-1016d72059bd · outbound

This paper cites Trajectory Flow Matching with Applications to Clinical Time Series Modelling,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Trajectory Flow Matching with Applications to Clinical Time Series Modelling,

Reference 23

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Observation 9f4488c2-6b5c-4431-ac8b-7e8abd3774af · outbound

This paper cites Streaming Flow Policy: Simplifying diffusion/flow- matching policies by treating action trajectories as flow trajectories,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Streaming Flow Policy: Simplifying diffusion/flow- matching policies by treating action trajectories as flow trajectories,

Reference 24

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Observation d5a5fa79-3cb0-4da2-818f-445d6d36cc5f · outbound

This paper cites VITA: Vision-to-Action Flow Matching Policy,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration VITA: Vision-to-Action Flow Matching Policy,

Reference 25

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Observation efa2236e-6976-4773-b98d-6e3499f9f78b · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration U-Net: Convolutional Networks for Biomedical Image Segmentation,

Reference 26

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Observation ed3a43ba-0f88-4faa-84a7-da9087975c46 · outbound

This paper cites Deep Residual Learning for Image Recognition,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Deep Residual Learning for Image Recognition,

Reference 27

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Observation 5bb95e1d-4e0d-4641-a499-441071e824a4 · outbound

This paper cites Deep spatial autoencoders for visuomotor learning,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Deep spatial autoencoders for visuomotor learning,

Reference 28

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Observation 7c2a6fe5-b0a0-4d6e-bf01-57aaeec3da57 · outbound

This paper cites FiLM: Visual Reasoning with a General Conditioning Layer,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration FiLM: Visual Reasoning with a General Conditioning Layer,

Reference 29

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Observation 352efeeb-767a-429d-b4b1-743069e2cb6e · outbound

This paper cites What Matters in Learning from Offline Human Demonstrations for Robot Manipulation,.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration What Matters in Learning from Offline Human Demonstrations for Robot Manipulation,

Reference 30

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Observation 46564354-cc51-4054-8861-a0224beddb10 · outbound

This paper cites Available: http://jmlr.org/papers/v26/23-1605.html.

Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration Available: http://jmlr.org/papers/v26/23-1605.html

Reference 2025

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Pith citing papers

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