Paper Citation Record · LEDGER

Instant Policy: In-Context Imitation Learning via Graph Diffusion

As of 15 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 7 inbound Pith citation observations for arXiv:2411.12633.

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

pith.paper-citation-record.v1
2411.12633 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:25:26.845296Z

measured 40 of 40 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:40:11.988891Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T21:57:25.836658Z

Reference resolution

33 of 33 outbound references displayed

verified exact0
verified fuzzy10
unresolved23
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 796f9b02-3721-4f33-870a-abf17a74fdfd · outbound

This paper cites We did so to match the distribution of object poses to the one present in our generated pseudo-demonstrations.

Instant Policy: In-Context Imitation Learning via Graph Diffusion We did so to match the distribution of object poses to the one present in our generated pseudo-demonstrations

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:27.128962Z

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.

Observation 9492b6e1-4cd7-4396-8d95-259a6ca5d9df · outbound

This paper cites Language Models are Few-Shot Learners.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Language Models are Few-Shot Learners

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.722637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18f36384-3626-43de-b693-6cf1b0113022 · outbound

This paper cites To add noise to the action expressed as (TEA ∈ SE(3), ag ∈ R, we first project TEA to se(3) using a Logmap, normalise the resulting vectors, add the noise as described by Ho et al.

Instant Policy: In-Context Imitation Learning via Graph Diffusion To add noise to the action expressed as (TEA ∈ SE(3), ag ∈ R, we first project TEA to se(3) using a Logmap, normalise the resulting vectors, add the noise as described by Ho et al

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:27.180790Z

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.

Observation 3abbaead-ece3-475c-a8b2-95f6db3e1e9f · outbound

This paper cites Keypoint Action Tokens Enable In-Context Imitation Learning in Robotics.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Keypoint Action Tokens Enable In-Context Imitation Learning in Robotics

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.735908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7681ad86-0246-462a-8580-7738111eeec4 · outbound

This paper cites OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs.

Instant Policy: In-Context Imitation Learning via Graph Diffusion OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.748427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02c78f3e-afb9-47fe-bc51-60df2bbe86c9 · outbound

This paper cites Vid2Robot: End-to-end Video-conditioned Policy Learning with Cross-Attention Transformers.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Vid2Robot: End-to-end Video-conditioned Policy Learning with Cross-Attention Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.756680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d03b771-ac98-40db-b3cc-fb84182fb893 · outbound

This paper cites Rrt-connect: An efficient approach to single-query path planning.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Rrt-connect: An efficient approach to single-query path planning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:27.241363Z

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.

Observation 4ce40d1f-5fac-4c22-b3a6-c3468627165b · outbound

This paper cites MediaPipe: A Framework for Building Perception Pipelines.

Instant Policy: In-Context Imitation Learning via Graph Diffusion MediaPipe: A Framework for Building Perception Pipelines

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.769444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2bb3a03-3b22-4178-9fda-9471e85e96af · outbound

This paper cites R+X: Retrieval and Execution from Everyday Human Videos.

Instant Policy: In-Context Imitation Learning via Graph Diffusion R+X: Retrieval and Execution from Everyday Human Videos

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.777937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29de9357-02ba-4f1d-94d0-b27e390e6ae6 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.781908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 939d8af2-bf54-4285-a436-95adbe1f3bdc · outbound

This paper cites Body Transformer: Leveraging Robot Embodiment for Policy Learning.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Body Transformer: Leveraging Robot Embodiment for Policy Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.785876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69f39d95-0300-47d4-9846-4c05387ed765 · outbound

This paper cites Denoising Diffusion Implicit Models.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Denoising Diffusion Implicit Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.794057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12e6a9d6-f1a2-48dd-b6e4-6457852dbcdc · outbound

This paper cites Se (3)-diffusionfields: Learning smooth cost functions for joint grasp and motion optimization through diffusion.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Se (3)-diffusionfields: Learning smooth cost functions for joint grasp and motion optimization through diffusion

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:27.229553Z

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.

Observation ebeb2642-3217-4e2e-9815-947f075335fa · outbound

This paper cites A system for learning continuous human-robot interactions from human-human demonstrations.

Instant Policy: In-Context Imitation Learning via Graph Diffusion A system for learning continuous human-robot interactions from human-human demonstrations

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:27.218263Z

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.

Observation 64c414b1-145b-4ae0-8427-6c760357f59f · outbound

This paper cites Few-Shot In-Context Imitation Learning via Implicit Graph Alignment.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Few-Shot In-Context Imitation Learning via Implicit Graph Alignment

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.805738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 296cc649-8b01-46da-920b-48b6b74b5b43 · outbound

This paper cites Scaling Robot Learning with Semantically Imagined Experience.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Scaling Robot Learning with Semantically Imagined Experience

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.809612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffee8b5a-3d7e-499e-87d0-6535dd504417 · outbound

This paper cites One-Shot Imitation Learning with Invariance Matching for Robotic Manipulation.

Instant Policy: In-Context Imitation Learning via Graph Diffusion One-Shot Imitation Learning with Invariance Matching for Robotic Manipulation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.813332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3cd785a-d24d-48f2-a5b7-3f35103b0d57 · outbound

This paper cites Formally, the local encoder encodes the dense point cloud into a set of feature vectors together with their associated positions as: {F i, pi}M i=1 = ϕ(P ).

Instant Policy: In-Context Imitation Learning via Graph Diffusion Formally, the local encoder encodes the dense point cloud into a set of feature vectors together with their associated positions as: {F i, pi}M i=1 = ϕ(P )

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:27.206077Z

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.

Observation 733e6939-73de-4349-aeab-a50c3404ecec · outbound

This paper cites It samples M centroids from the dense point cloud and embeds the local geometries around them into feature vectors of size.

Instant Policy: In-Context Imitation Learning via Graph Diffusion It samples M centroids from the dense point cloud and embeds the local geometries around them into feature vectors of size

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:27.193569Z

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.

Observation ef159b82-91ed-4bc1-b26a-0c5ad921bdfb · outbound

This paper cites We ensure that the spacing between the subsequent spaces is constant and uniform (1cm and 3 degrees, same as used for the normalisation of actions).

Instant Policy: In-Context Imitation Learning via Graph Diffusion We ensure that the spacing between the subsequent spaces is constant and uniform (1cm and 3 degrees, same as used for the normalisation of actions)

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:27.166130Z

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.

Observation 26f71516-3800-4246-974a-6fa8adab294f · outbound

This paper cites 5 days on a single NVIDIA GeForce RTX 3080-ti) followed by a 50K steps learning rate cool-down period.

Instant Policy: In-Context Imitation Learning via Graph Diffusion 5 days on a single NVIDIA GeForce RTX 3080-ti) followed by a 50K steps learning rate cool-down period

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:27.153664Z

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.

Observation fcb6e922-4590-43c4-9732-52a3243ef841 · outbound

This paper cites We did so to ensure that the demonstrations did not have arbitrary motions that would not be captured by our observations of segmented point clouds and end-effector poses.

Instant Policy: In-Context Imitation Learning via Graph Diffusion We did so to ensure that the demonstrations did not have arbitrary motions that would not be captured by our observations of segmented point clouds and end-effector poses

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:27.141269Z

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.

Observation c7ae33bb-9686-4a5b-9e45-8e55f6b27ae3 · outbound

This paper cites an unresolved cited work.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:25:27.116220Z

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.

Observation b6af8415-763d-47ec-a43d-d37190bba99f · outbound

This paper cites Layer Normalization.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Layer Normalization

Reference 1987

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.712928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c47203b-47f2-40e5-aa4b-b497130f5aca · outbound

This paper cites Decoupled Weight Decay Regularization.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Decoupled Weight Decay Regularization

Reference 2000

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.765518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a646d45d-2961-4f66-a583-25a3b3f7731e · outbound

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

Instant Policy: In-Context Imitation Learning via Graph Diffusion Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.731477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34b2a808-e94e-4873-8a5a-5d319a4d7804 · outbound

This paper cites In-Context Imitation Learning via Next-Token Prediction.

Instant Policy: In-Context Imitation Learning via Graph Diffusion In-Context Imitation Learning via Next-Token Prediction

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.740299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b39200c2-2cf2-444d-b841-311cddd101e3 · outbound

This paper cites Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.789987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c168d1e-9887-4c89-8c23-29630f9be319 · outbound

This paper cites MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations.

Instant Policy: In-Context Imitation Learning via Graph Diffusion MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.773732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 597558e3-8790-41c6-8962-0cd8f9fcc6a6 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Instant Policy: In-Context Imitation Learning via Graph Diffusion ShapeNet: An Information-Rich 3D Model Repository

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.727220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee093bb6-c167-423e-8402-53d3bc29eb8a · outbound

This paper cites Perceiver IO: A General Architecture for Structured Inputs & Outputs.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Perceiver IO: A General Architecture for Structured Inputs & Outputs

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.752562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a6f10e6-a07d-4fdb-b60c-1b85996fc291 · outbound

This paper cites Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models.

Instant Policy: In-Context Imitation Learning via Graph Diffusion Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.717735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bccbf49c-2203-4dc7-b245-4db9c13cc7ba · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Instant Policy: In-Context Imitation Learning via Graph Diffusion Gaussian Error Linear Units (GELUs)

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-12T17:25:26.744671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 4bfb403d-e5a3-4d83-b211-2bb9e5bff386 · inbound

GAF: Gaussian Action Field as a 4D Representation for Dynamic World Modeling in Robotic Manipulation cites this paper.

GAF: Gaussian Action Field as a 4D Representation for Dynamic World Modeling in Robotic Manipulation Instant Policy: In-Context Imitation Learning via Graph Diffusion

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-25T07:50:29.247953Z

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.

Observation 1f37b292-8899-46f7-ae87-a4844274bbf0 · inbound

Knowledge-Driven Imitation Learning: Enabling Generalization Across Diverse Conditions cites this paper.

Knowledge-Driven Imitation Learning: Enabling Generalization Across Diverse Conditions Instant Policy: In-Context Imitation Learning via Graph Diffusion

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T22:40:11.988891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2b7ef85-da9c-4a60-b6d7-e6c22dde23b2 · inbound

Learning in ImaginationLand: Omnidirectional Policies through 3D Generative Models (OP-Gen) cites this paper.

Learning in ImaginationLand: Omnidirectional Policies through 3D Generative Models (OP-Gen) Instant Policy: In-Context Imitation Learning via Graph Diffusion

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T00:02:31.103915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc756b72-5d4d-4090-afa6-a22a82fce9ce · inbound

MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos cites this paper.

MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos Instant Policy: In-Context Imitation Learning via Graph Diffusion

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T18:51:36.013303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a2d9124-d4a4-453b-afc8-488089b5ce07 · inbound

Point Cloud Sequence Encoding for Material-conditioned Graph Network Simulators cites this paper.

Point Cloud Sequence Encoding for Material-conditioned Graph Network Simulators Instant Policy: In-Context Imitation Learning via Graph Diffusion

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:09:41.469757Z

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.

Observation d8754717-19b1-4088-ba00-8c5c3f60e225 · inbound

SynthICL: Scalable In-context Imitation Learning with Synthetic Data cites this paper.

SynthICL: Scalable In-context Imitation Learning with Synthetic Data Instant Policy: In-Context Imitation Learning via Graph Diffusion

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:57:25.838127Z

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.

Observation 3039ad2f-5de8-4112-bbd9-3bf61879f57a · inbound

Try Once, Then Optimal: De-Redundified Procedure Memory for Cross-Episode Exploration Amortization cites this paper.

Try Once, Then Optimal: De-Redundified Procedure Memory for Cross-Episode Exploration Amortization Instant Policy: In-Context Imitation Learning via Graph Diffusion

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-30T15:27:16.652920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.