Paper Citation Record · LEDGER

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation

As of 7 August 2026, this Paper Citation Record lists 100 of 135 outbound references and 6 inbound Pith citation observations for arXiv:2506.09284.

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

pith.paper-citation-record.v1
2506.09284 v2

Coverage vector

measured 100 of 135 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:58:54.442710Z

measured 106 of 106 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:55:43.237396Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:29:51.374178Z

Reference resolution

100 of 135 outbound references displayed

verified exact1
verified fuzzy8
unresolved91
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 19e8b9a2-f1fa-4670-a93f-2dea150ae7ab · outbound

This paper cites To afford or not to afford: A new formalization of affordances toward affordance-based robot control,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation To afford or not to afford: A new formalization of affordances toward affordance-based robot control,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:30.681659Z

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Observation bb9ee850-dc16-4e3c-9c0a-708d2647d80f · outbound

This paper cites Affordances from human videos as a versatile representation for robotics,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Affordances from human videos as a versatile representation for robotics,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:31.351855Z

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Observation b39fab20-d013-4a93-a4dc-970afa3c8729 · outbound

This paper cites Ditto in the house: Building articulation models of indoor scenes through interactive perception,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Ditto in the house: Building articulation models of indoor scenes through interactive perception,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:33.794425Z

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Observation e3943fe9-5529-48eb-afe4-0d0002898911 · outbound

This paper cites Affordances in psychology, neuroscience, and robotics: A survey,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Affordances in psychology, neuroscience, and robotics: A survey,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:35.359203Z

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Observation be99691a-7fa5-476f-87d5-1a06caf53f45 · outbound

This paper cites A brief review of affordance in robotic manipulation research,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation A brief review of affordance in robotic manipulation research,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:36.382491Z

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Observation e2fe8bfa-5788-4923-b167-3981c973a895 · outbound

This paper cites Visual affordance and function understanding: A survey,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Visual affordance and function understanding: A survey,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:39.806659Z

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Observation d3deb891-c68f-4445-9f43-d683ce299352 · outbound

This paper cites A survey of visual affordance recognition based on deep learning,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation A survey of visual affordance recognition based on deep learning,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:40.076269Z

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Observation c065643b-b675-44f5-b9dc-3e942032f51f · outbound

This paper cites A survey of semantic reasoning frameworks for robotic systems,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation A survey of semantic reasoning frameworks for robotic systems,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:41.466880Z

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Observation 61f90d88-5b70-4eb9-b8fe-f39e30a8cd32 · outbound

This paper cites Recent advances of deep robotic affordance learning: a reinforcement learning perspective,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Recent advances of deep robotic affordance learning: a reinforcement learning perspective,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:43.490512Z

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Observation af0d3b4f-4186-444f-85bb-fe16864ce4a7 · outbound

This paper cites Gpt-4 technical report,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Gpt-4 technical report,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:43.674169Z

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Observation d666e44e-417f-4b3e-a866-387c9faf4d04 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Gemini: A Family of Highly Capable Multimodal Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:43.839685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0a8176c-0b00-48b6-be42-b3cd498f04d8 · outbound

This paper cites GPT-4 Technical Report.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation GPT-4 Technical Report

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:44.003575Z

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Unavailable: canonical work link unavailable.

Observation 7790e4cf-6e35-4d27-87d0-6dc71eedc310 · outbound

This paper cites Emerging properties in self-supervised vision trans- formers,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Emerging properties in self-supervised vision trans- formers,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:44.137035Z

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Observation 5ff11940-2363-4524-909a-d9bf2fb1d55e · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation DINOv2: Learning Robust Visual Features without Supervision

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:44.266795Z

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Observation e3f79409-8a4b-4cfd-99ca-dd4a6fd9b044 · outbound

This paper cites Grounded Affordance from Exocentric View.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Grounded Affordance from Exocentric View

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:44.421123Z

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Observation 619e33a8-d6fb-4bdb-89b3-b14a80874923 · outbound

This paper cites Droid: A large-scale in-the-wild robot manipulation dataset,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Droid: A large-scale in-the-wild robot manipulation dataset,

Reference 16

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Source-reported events for the cited work

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Observation ddee7633-09c5-41ca-ac4c-8f2167010cc2 · outbound

This paper cites Learning state representations with robotic priors,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Learning state representations with robotic priors,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:44.647200Z

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Observation 84773c6e-b52a-45bc-9697-0aa7af8612f9 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Learning transferable visual models from natural language supervision,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:44.715651Z

Source-reported events for the cited work

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Observation eab956e4-f9d9-4873-b89f-0cd279c3ee3c · outbound

This paper cites The theory of affordances,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation The theory of affordances,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:44.807451Z

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Observation cb289901-aac1-4415-a2fd-840416977ec2 · outbound

This paper cites Norman, The design of everyday things: Revised and expanded edition.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Norman, The design of everyday things: Revised and expanded edition

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:44.902308Z

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Observation 5bcaf4e7-ff37-4219-8cce-6c505bf3052b · outbound

This paper cites Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic Grasping.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic Grasping

Reference 21

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Source-reported events for the cited work

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Observation af89a593-db44-45ba-931d-46b71871e2f3 · outbound

This paper cites Self-supervised visual descriptor learning for dense correspondence,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Self-supervised visual descriptor learning for dense correspondence,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:45.180106Z

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Observation 31b503e7-d612-4b6f-92eb-46e297c14f94 · outbound

This paper cites Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:45.337097Z

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Observation 8b189007-d278-4c7e-a9e4-a207bea059a5 · outbound

This paper cites kpam: Keypoint affordances for category-level robotic manipulation,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation kpam: Keypoint affordances for category-level robotic manipulation,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:45.607094Z

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Observation 75531195-ff43-4430-bf1e-d7a098f0b1f2 · outbound

This paper cites Unsupervised learning of object key- points for perception and control,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Unsupervised learning of object key- points for perception and control,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:45.753418Z

Source-reported events for the cited work

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Observation eb92a658-efb5-4168-ac6a-f941aead6c29 · outbound

This paper cites Keto: Learning keypoint representations for tool manipulation,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Keto: Learning keypoint representations for tool manipulation,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:45.870214Z

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Observation e6167ff1-e089-417a-818b-e08a47e9a6d0 · outbound

This paper cites Learning rope manipulation policies using dense object descriptors trained on synthetic depth data,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Learning rope manipulation policies using dense object descriptors trained on synthetic depth data,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:45.964437Z

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Observation 62845579-1b71-4cbd-93f7-5ba61f1acf45 · outbound

This paper cites Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:46.127638Z

Source-reported events for the cited work

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Observation c4709331-e432-4906-b13a-89224588015d · outbound

This paper cites Unsupervised learning of visual 3d keypoints for control,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Unsupervised learning of visual 3d keypoints for control,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:46.208571Z

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Observation a2b7d1aa-792a-49ce-a950-366fe7770b4c · outbound

This paper cites Neural descriptor fields: Se (3)- equivariant object representations for manipulation,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Neural descriptor fields: Se (3)- equivariant object representations for manipulation,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:46.366078Z

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Observation 046229ac-65d4-49b5-8dc5-18e1c2016a6f · outbound

This paper cites Se (3)-equivariant relational rearrangement with neural descriptor fields,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Se (3)-equivariant relational rearrangement with neural descriptor fields,

Reference 31

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Observation 08c75aba-1f5a-462a-a17e-db6ff134cfbc · outbound

This paper cites RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation

Reference 32

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Observation 362749c5-09e4-474f-ba88-b7c7792bfc25 · outbound

This paper cites Local neural descriptor fields: Locally conditioned object represen- tations for manipulation,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Local neural descriptor fields: Locally conditioned object represen- tations for manipulation,

Reference 33

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Observation 65bfca8a-11c0-4bb8-b67a-6083fa6087ae · outbound

This paper cites Any-point Trajectory Modeling for Policy Learning.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Any-point Trajectory Modeling for Policy Learning

Reference 34

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Observation 39649e02-f077-4e1f-8b5b-7c3de42f0572 · outbound

This paper cites Track2act: Predicting point tracks from internet videos enables diverse zero-shot robot manipulation,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Track2act: Predicting point tracks from internet videos enables diverse zero-shot robot manipulation,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:47.100054Z

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Observation b703bcce-d429-41b3-958e-835982ce29ca · outbound

This paper cites An affordance keypoint detection network for robot manipulation,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation An affordance keypoint detection network for robot manipulation,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:47.261056Z

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Observation f1461771-fcaa-4893-b5be-fa47ac2586dc · outbound

This paper cites ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:47.369469Z

Source-reported events for the cited work

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Observation 34884d01-2631-4290-9ba7-571277ae32d1 · outbound

This paper cites Affordance detection of tool parts from geometric features,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Affordance detection of tool parts from geometric features,

Reference 38

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Observation 898f8bda-842e-4b37-8f9d-bfbec3f46b91 · outbound

This paper cites Affordance detection for task-specific grasping using deep learning,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Affordance detection for task-specific grasping using deep learning,

Reference 39

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Observation a46c268c-89fc-4090-ab79-236372b9e7c0 · outbound

This paper cites Object-based affordances detection with convolutional neural net- works and dense conditional random fields,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Object-based affordances detection with convolutional neural net- works and dense conditional random fields,

Reference 40

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Observation 762202d1-d371-484f-95aa-85e19c20bb9d · outbound

This paper cites Affordancenet: An end-to-end deep learning approach for object affordance detection,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Affordancenet: An end-to-end deep learning approach for object affordance detection,

Reference 41

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Observation 40121d3e-509a-40b4-b30d-02dc754a00c7 · outbound

This paper cites Toward affordance detection and ranking on novel objects for real-world robotic manip- ulation,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Toward affordance detection and ranking on novel objects for real-world robotic manip- ulation,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:47.896212Z

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Observation ae2a15ce-b5bb-4875-bfce-48669aa85b37 · outbound

This paper cites Learning dexterous grasping with object-centric visual affordances,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Learning dexterous grasping with object-centric visual affordances,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:48.049614Z

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Observation cf50cacb-9ed4-4bee-b130-993bd2beba3a · outbound

This paper cites Affordance learning for end-to-end visuomotor robot control,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Affordance learning for end-to-end visuomotor robot control,

Reference 44

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Observation 29c7450f-8d75-479b-9fa6-ba481f2b20d7 · outbound

This paper cites Affordance learning from play for sample-efficient policy learning,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Affordance learning from play for sample-efficient policy learning,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:48.250001Z

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Observation c23841ac-e208-4f35-b0f5-ea74122bd413 · outbound

This paper cites Visual affordance pre- diction for guiding robot exploration,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Visual affordance pre- diction for guiding robot exploration,

Reference 46

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Observation f153e561-133b-454d-85e7-b83de4f01ad6 · outbound

This paper cites HRP: Human Affordances for Robotic Pre-Training.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation HRP: Human Affordances for Robotic Pre-Training

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:48.482260Z

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Observation b8ce8ea2-8810-4578-ad5d-f9ba4f7f4f18 · outbound

This paper cites Learning relational affordance models for robots in multi-object manipulation tasks,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Learning relational affordance models for robots in multi-object manipulation tasks,

Reference 48

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Observation b012a899-417e-481b-a26d-1a518759dfe7 · outbound

This paper cites Affordance-based grasping and manipulation in real world applications,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Affordance-based grasping and manipulation in real world applications,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:48.707660Z

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Observation 02107307-a024-4cb4-a64b-bf9a40c915a6 · outbound

This paper cites Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross- domain image matching,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross- domain image matching,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:48.781486Z

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Observation 4c791151-5b18-406d-88ae-1c10ffc337ae · outbound

This paper cites Metagrasp: Data efficient grasping by affordance interpreter network,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Metagrasp: Data efficient grasping by affordance interpreter network,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:48.869424Z

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Observation 3970c5a5-3ac6-4d1a-ab29-608314cf3452 · outbound

This paper cites Learning affordance space in physical world for vision-based robotic object manipulation,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Learning affordance space in physical world for vision-based robotic object manipulation,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:48.971088Z

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Observation 8285cf01-6602-43d6-aaaa-3c9c59c3bf2e · outbound

This paper cites Learning multi- object dense descriptor for autonomous goal-conditioned grasping,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Learning multi- object dense descriptor for autonomous goal-conditioned grasping,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:49.052562Z

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Observation fd05c41d-a50c-4561-8d68-8a8efd295ad1 · outbound

This paper cites Deep affordance foresight: Planning through what can be done in the future,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Deep affordance foresight: Planning through what can be done in the future,

Reference 54

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Observation d236ac2e-d78a-4397-a83d-a8604444a8e5 · outbound

This paper cites Where2act: From pixels to actions for articulated 3d objects,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Where2act: From pixels to actions for articulated 3d objects,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:49.317670Z

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Observation ab0ee92c-2cc0-4092-b626-807e5d2059c9 · outbound

This paper cites Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:49.482082Z

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Observation b1ddd6cd-2c1e-4353-8fb9-accd83001d87 · outbound

This paper cites Grounding Language with Visual Affordances over Unstructured Data.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Grounding Language with Visual Affordances over Unstructured Data

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:49.567636Z

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Observation 277cdb4a-ca8b-442e-b3f0-84faf4a275b9 · outbound

This paper cites Learning generalizable dexterous manipulation from human grasp affordance,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Learning generalizable dexterous manipulation from human grasp affordance,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:49.666570Z

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Observation 09076003-937e-43be-9949-66c444b7c9b2 · outbound

This paper cites Learning affordance grounding from exocentric images,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Learning affordance grounding from exocentric images,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:49.775313Z

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Observation 7606ed3e-3e38-4ba8-928e-8b8bbf197f45 · outbound

This paper cites Locate: Localize and transfer object parts for weakly supervised affordance grounding,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Locate: Localize and transfer object parts for weakly supervised affordance grounding,

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:49.889545Z

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Observation 03475642-ee76-4a98-8112-518133140a07 · outbound

This paper cites Affordpose: A large- scale dataset of hand-object interactions with affordance-driven hand pose,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Affordpose: A large- scale dataset of hand-object interactions with affordance-driven hand pose,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:50.021030Z

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Observation d9d4058e-15ec-4374-8b99-4ac8ca178378 · outbound

This paper cites 3d affordancenet: A benchmark for visual object affordance understanding,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation 3d affordancenet: A benchmark for visual object affordance understanding,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:50.183998Z

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Observation 2f03fc6a-70b4-4c67-b990-e79d022a2f99 · outbound

This paper cites GIFT: Generalizable Interaction-aware Functional Tool Affordances without Labels.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation GIFT: Generalizable Interaction-aware Functional Tool Affordances without Labels

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:50.356269Z

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Observation 781c4177-2bf8-4c71-9548-8112df7bae7d · outbound

This paper cites RRL: Resnet as representation for Reinforcement Learning.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation RRL: Resnet as representation for Reinforcement Learning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:50.507923Z

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Observation 0ec3b6d5-215b-4888-8615-1ab1c77f80b7 · outbound

This paper cites The Surprising Effectiveness of Representation Learning for Visual Imitation.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation The Surprising Effectiveness of Representation Learning for Visual Imitation

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:50.652147Z

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Observation 17f43029-cc7c-4451-97c5-be6fe8275061 · outbound

This paper cites The unsurprising effectiveness of pre-trained vision models for control,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation The unsurprising effectiveness of pre-trained vision models for control,

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:50.782536Z

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Observation 3da5337c-0210-42f4-ba89-2f6e58a19f2d · outbound

This paper cites Masked Visual Pre-training for Motor Control.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Masked Visual Pre-training for Motor Control

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:50.924401Z

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Observation 2ba4dd18-59b0-432c-8c06-892b0e3577da · outbound

This paper cites Real-world robot learning with masked visual pre-training,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Real-world robot learning with masked visual pre-training,

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:51.094252Z

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Observation 168fa19c-c39b-4fd3-91ba-5a5495ae9509 · outbound

This paper cites VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:51.297606Z

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Observation 7c8e226f-2a71-4d67-918c-68831c562caf · outbound

This paper cites Where are we in the search for an artificial visual cortex for embodied intelligence?.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Where are we in the search for an artificial visual cortex for embodied intelligence?

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:51.450409Z

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Observation b4b153d4-0a61-4d9e-b513-388c100d7c3f · outbound

This paper cites What Makes Pre-Trained Visual Representations Successful for Robust Manipulation?.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation What Makes Pre-Trained Visual Representations Successful for Robust Manipulation?

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:51.628421Z

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Observation f34737fc-71d5-4eb4-af7c-62dd024ddbb8 · outbound

This paper cites Offline visual represen- tation learning for embodied navigation,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Offline visual represen- tation learning for embodied navigation,

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:51.721888Z

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Observation 960851e6-defb-451b-bcef-81884104afa2 · outbound

This paper cites R3M: A Universal Visual Representation for Robot Manipulation.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation R3M: A Universal Visual Representation for Robot Manipulation

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:51.906420Z

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Observation 1eba31b4-7702-4fa7-92a2-68d39581b209 · outbound

This paper cites Language-Driven Representation Learning for Robotics.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Language-Driven Representation Learning for Robotics

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:52.096173Z

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Observation 0035884c-289e-4e54-b2e5-46a31acf3de3 · outbound

This paper cites Liv: Language-image representations and rewards for robotic control,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Liv: Language-image representations and rewards for robotic control,

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:52.271406Z

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Observation 1dffb014-20d6-4ff4-b171-f53a5e01ad6c · outbound

This paper cites Simple but effective: Clip embeddings for embodied ai,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Simple but effective: Clip embeddings for embodied ai,

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:52.402855Z

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Observation b9d61ca8-86ce-4473-82bf-2a4c10d74ec2 · outbound

This paper cites Can foundation models perform zero-shot task specification for robot manipulation?.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Can foundation models perform zero-shot task specification for robot manipulation?

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:59:04.169964Z

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Observation 55851907-02d3-4937-9092-64624485edbd · outbound

This paper cites Cliport: What and where pathways for robotic manipulation,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Cliport: What and where pathways for robotic manipulation,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:59:04.002602Z

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Observation e918e6f7-52a9-4835-96fd-c42b9129e3dd · outbound

This paper cites Spawnnet: Learning generalizable visuomotor skills from pre-trained network,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Spawnnet: Learning generalizable visuomotor skills from pre-trained network,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:59:03.854511Z

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Observation a52aad4e-5e76-44ac-a4d1-c34c65cb6eb8 · outbound

This paper cites GenDP: 3d semantic fields for category-level generalizable diffusion policy,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation GenDP: 3d semantic fields for category-level generalizable diffusion policy,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:59:03.714794Z

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Observation f967932b-d908-4fc6-8bc9-2335c91f3037 · outbound

This paper cites Robots Pre-train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Datasets.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Robots Pre-train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Datasets

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:52.920607Z

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Observation 1a770ebd-471e-48d7-bb2c-63f0d92aafb2 · outbound

This paper cites Otter: A vision-language-action model with text-aware visual feature extraction,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Otter: A vision-language-action model with text-aware visual feature extraction,

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:53.028914Z

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Observation 9b015a26-9eab-4b09-ab92-d10730fb916a · outbound

This paper cites Eyes wide shut? exploring the visual shortcomings of multimodal llms,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Eyes wide shut? exploring the visual shortcomings of multimodal llms,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:59:03.552760Z

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Observation 6097c010-d01f-4301-bab4-b3ae464669e7 · outbound

This paper cites Winoground: Probing vision and language models for visio-linguistic compositionality,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Winoground: Probing vision and language models for visio-linguistic compositionality,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:59:03.401089Z

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Observation 4fc9eb35-f6f9-44eb-928d-53a2da57c95b · outbound

This paper cites When and why vision-language models behave like bags-of-words, and what to do about it?.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation When and why vision-language models behave like bags-of-words, and what to do about it?

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:59:03.255481Z

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Observation 6b3b1b70-27e1-4782-ad42-2c332e9f47d9 · outbound

This paper cites Sugarcrepe: Fixing hackable benchmarks for vision-language com- positionality,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Sugarcrepe: Fixing hackable benchmarks for vision-language com- positionality,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:59:03.113881Z

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Observation 711095f9-707b-4ef9-a73c-36d951d0a4f5 · outbound

This paper cites Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:53.446033Z

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Observation 5c2bc97e-5099-4d5f-a048-f7d04c57ed39 · outbound

This paper cites Foundation Models in Robotics: Applications, Challenges, and the Future.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Foundation Models in Robotics: Applications, Challenges, and the Future

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:53.510632Z

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Observation 76fa5d92-a3ce-4484-b69b-8f9b89d44e92 · outbound

This paper cites Real-World Robot Applications of Foundation Models: A Review.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Real-World Robot Applications of Foundation Models: A Review

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:53.560629Z

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Observation e93e8ece-734e-48d8-ac24-14f4972fb4fd · outbound

This paper cites Foundation Models for Decision Making: Problems, Methods, and Opportunities.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Foundation Models for Decision Making: Problems, Methods, and Opportunities

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:53.629901Z

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Observation 05e3e450-66f9-4da2-bb16-59a5c5e6eafd · outbound

This paper cites CoPa: General Robotic Manipulation through Spatial Constraints of Parts with Foundation Models.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation CoPa: General Robotic Manipulation through Spatial Constraints of Parts with Foundation Models

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:53.681208Z

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Observation 9650ecbe-c9d9-45a7-b74f-d7da9e6b17ae · outbound

This paper cites MOKA: Open-World Robotic Manipulation through Mark-Based Visual Prompting.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation MOKA: Open-World Robotic Manipulation through Mark-Based Visual Prompting

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:53.781859Z

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Observation e5c1427f-7675-42e3-8e7c-fe077f9071ec · outbound

This paper cites PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:53.856037Z

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Observation f7a13579-681a-48dd-9bce-fc3b01b1feea · outbound

This paper cites Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:53.946964Z

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Observation 212b8b0c-8cee-4d8d-9395-ed48d4d60a43 · outbound

This paper cites Video Language Planning.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Video Language Planning

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:54.032686Z

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Observation bf6f62ab-99f5-4a2a-b8b4-01ab94f7d42b · outbound

This paper cites 3d-llm: Injecting the 3d world into large language models,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation 3d-llm: Injecting the 3d world into large language models,

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:54.106707Z

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Observation e1a5d62c-6a73-4296-9ebb-969f44d1c380 · outbound

This paper cites Spatialvlm: Endowing vision-language models with spatial reasoning capabilities,.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Spatialvlm: Endowing vision-language models with spatial reasoning capabilities,

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:54.198673Z

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Observation 93201b58-411a-462f-a005-259eef537302 · outbound

This paper cites VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:54.287250Z

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Observation fc97f1a8-e40b-48ed-a702-05e50757c3c4 · outbound

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UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:54.362866Z

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Observation c35d9411-e81c-49cf-b1e6-df87bda53714 · outbound

This paper cites Physically Grounded Vision-Language Models for Robotic Manipulation.

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation Physically Grounded Vision-Language Models for Robotic Manipulation

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:54.442710Z

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Pith citing papers

Observation 6cd554e9-e642-4c18-bc2d-36fcc1ccb097 · inbound

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O$^3$Afford: One-Shot 3D Object-to-Object Affordance Grounding for Generalizable Robotic Manipulation UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-04T23:55:43.237396Z

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Observation 56a9b232-db5b-4a71-8a53-55d83c6a72d2 · inbound

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FUNCanon: Learning Pose-Aware Action Primitives via Functional Object Canonicalization for Generalizable Robotic Manipulation UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:15:41.936416Z

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Observation 4a9f8d5c-7ad7-447b-a482-656535a2962f · inbound

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AFFORD2ACT: Affordance-Guided Automatic Keypoint Selection for Generalizable and Lightweight Robotic Manipulation UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-18T10:21:15.252945Z

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Observation 4043f4c3-6df1-4da3-9d13-eb45b50bc92e · inbound

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PhysGraph: A Physics-aware 3D Scene Graph for Perception and Reasoning UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-02T23:27:27.449919Z

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Observation 21bbfbdb-2721-446c-b993-90b9053c1ea8 · inbound

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RelAfford6D: Relational 6D Affordance Graphs for Constraint-Driven Robotic Manipulation UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:29:51.375616Z

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Observation a4bc107a-92b2-4b83-81c2-58893c2c8a04 · inbound

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Learning 3D Affordances for Blade Insertion in Cluttered Stowing UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-12T11:41:59.158887Z

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