AFUN: Towards an Affordance Foundation Model for Functionality Understanding | Paper Citation Record

Observation 26b56391-4fe7-4a03-90fb-f94f533106f1 · outbound

This paper cites AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-01T23:36:22.841587Z

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Observation f6d414d2-4b85-4045-b3f7-915538f3bd2f · outbound

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

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Affordances from human videos as a versatile representation for robotics

Reference 2

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Observation 84bc78b2-7689-46cc-9b05-2088927a271a · outbound

This paper cites Qwen3-VL Technical Report.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Qwen3-VL Technical Report

Reference 3

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Observation 0fe6e695-4b65-4063-8a98-e8e586feb406 · outbound

This paper cites HOT3D: Hand and object tracking in 3D from egocentric multi-view videos.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding HOT3D: Hand and object tracking in 3D from egocentric multi-view videos

Reference 4

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Observation a0db5fd9-2f34-4b33-a25a-ec953f53216c · outbound

This paper cites Track2Act: Predicting point tracks from internet videos enables generalizable robot manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Track2Act: Predicting point tracks from internet videos enables generalizable robot manipulation

Reference 5

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Observation 1d141317-78ea-421c-bba5-4837376d6d88 · outbound

This paper cites — IEEE.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding — IEEE

Reference 6

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Observation b10be412-34f5-4961-8a81-24a6db2ebf0b · outbound

This paper cites VidBot: Learning generalizable 3D actions from in-the-wild 2D human videos for zero-shot robotic manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding VidBot: Learning generalizable 3D actions from in-the-wild 2D human videos for zero-shot robotic manipulation

Reference 7

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Observation 1fdf7b90-ba27-4124-891d-7bb98e0231c5 · outbound

This paper cites G3Flow: Generative 3D semantic flow for pose-aware and generalizable object manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding G3Flow: Generative 3D semantic flow for pose-aware and generalizable object manipulation

Reference 8

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Observation 1bb594e8-53d4-4465-8df6-6e0e34a07a51 · outbound

This paper cites 3d-affordancellm: Harnessing large language models for open-vocabulary affordance detection in 3d worlds.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding 3d-affordancellm: Harnessing large language models for open-vocabulary affordance detection in 3d worlds

Reference 9

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Observation 700ce1bf-a673-4bc7-88d8-d6ecab4c7264 · outbound

This paper cites GanHand: Predicting human grasp affordances in multi-object scenes.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding GanHand: Predicting human grasp affordances in multi-object scenes

Reference 10

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Observation 0d19eac0-1ec0-42ac-a770-606ef1b8f0a5 · outbound

This paper cites Rescaling egocentric vision: Collection, pipeline and challenges for EPIC-KITCHENS-100.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Rescaling egocentric vision: Collection, pipeline and challenges for EPIC-KITCHENS-100

Reference 11

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Observation e6131330-580c-4317-bdf4-77fc2d849823 · outbound

This paper cites SceneFun3D: Fine-grained functionality and affordance understanding in 3D scenes.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding SceneFun3D: Fine-grained functionality and affordance understanding in 3D scenes

Reference 12

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Observation f285fa28-b06a-498e-87a6-07f3ad1bce4f · outbound

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

AFUN: Towards an Affordance Foundation Model for Functionality Understanding 3d affordancenet: A benchmark for visual object affordance understanding

Reference 13

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Observation 7e851b65-5cb6-4bcd-b4c7-190b9fb4f7ae · outbound

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

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Affordancenet: An end-to-end deep learning ap- proach for object affordance detection

Reference 14

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Observation 93b7695d-ce97-4764-b80f-9ba0a557b8be · outbound

This paper cites Eisner, H.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Eisner, H

Reference 16

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Observation 6c6f44e9-1c22-4b52-a550-3168892f722c · outbound

This paper cites RH20T: A Comprehensive Robotic Dataset for Learning Diverse Skills in One-Shot.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding RH20T: A Comprehensive Robotic Dataset for Learning Diverse Skills in One-Shot

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:36:22.837870Z

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Observation 4be2939d-d156-4188-b410-5d85096fb436 · outbound

This paper cites Near-optimal multi-robot motion planning with finite sampling,.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Near-optimal multi-robot motion planning with finite sampling,

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T14:22:18.477174Z

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Observation 775f7587-70f9-4521-8607-e9ea9bf28ce6 · outbound

This paper cites Poles of inaccessibility: A calculation algorithm for the remotest places on earth.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Poles of inaccessibility: A calculation algorithm for the remotest places on earth

Reference 19

Resolution: verified exact; doi, observed 2026-06-28T14:22:18.479124Z

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Observation cd3900ba-62ba-49a5-8bfb-e7d7f2c48cde · outbound

This paper cites Gibson.The Ecological Approach to Visual Perception.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Gibson.The Ecological Approach to Visual Perception

Reference 20

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Observation e4509e00-6c57-47d1-b169-d956c2aae01c · outbound

This paper cites Ego4D: Around the world in 3,000 hours of egocentric video.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Ego4D: Around the world in 3,000 hours of egocentric video

Reference 21

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Observation b8eed7a6-973b-4536-95fe-2a3747a86d53 · outbound

This paper cites Fsag: Enhancing human-to-dexterous-hand finger-specific affordance grounding via diffusion models, 2026.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Fsag: Enhancing human-to-dexterous-hand finger-specific affordance grounding via diffusion models, 2026

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:36:22.833015Z

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Observation 7c86a5da-1559-4e9c-9c4a-ca1522cf23ae · outbound

This paper cites Roboafford++: A generative ai-enhanced dataset for multimodal affordance learning in robotic manipulation and navigation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Roboafford++: A generative ai-enhanced dataset for multimodal affordance learning in robotic manipulation and navigation

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:36:22.812088Z

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Observation 7b122928-2de5-4265-94ce-175e1a12664a · outbound

This paper cites 2handedafforder: Learning precise actionable bimanual affordances from human videos.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding 2handedafforder: Learning precise actionable bimanual affordances from human videos

Reference 24

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Observation 83c7ed4f-b846-40ef-a3fd-9f3c4c43b0bf · outbound

This paper cites Robomind 2.0: A multimodal, bimanual mobile manipulation dataset for generalizable embodied intelligence.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Robomind 2.0: A multimodal, bimanual mobile manipulation dataset for generalizable embodied intelligence

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:36:22.794021Z

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Observation 9f9e200e-6f2a-49b1-aa85-738a53e43478 · outbound

This paper cites Dreher, T.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Dreher, T

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T14:22:18.472939Z

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Observation 4d81a723-784b-450e-b437-16eb79486eb4 · outbound

This paper cites https://doi.org/10.1109/iros60139.2025.11247690.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding https://doi.org/10.1109/iros60139.2025.11247690

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T14:22:18.488720Z

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Observation e43b37e4-8ccf-46ca-9633-b77188fbeabd · outbound

This paper cites an unresolved cited work.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Unresolved cited work

Reference 28

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Observation 0f111694-71b5-40ab-b21f-26fea7d90d48 · outbound

This paper cites INTRA: Interaction relationship-aware weakly supervised affordance grounding.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding INTRA: Interaction relationship-aware weakly supervised affordance grounding

Reference 29

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Observation d2317434-da50-4484-be7d-677cf885582b · outbound

This paper cites AffordanceSAM: Segment Anything Once More in Affordance Grounding.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding AffordanceSAM: Segment Anything Once More in Affordance Grounding

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-13T01:20:01.599725Z

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Observation 14fcc052-b9b5-41f8-8424-3638d0d6ccf8 · outbound

This paper cites an unresolved cited work.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Unresolved cited work

Reference 31

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Observation 698dd70c-5f37-416e-97f5-667ab380ad9c · outbound

This paper cites Robo- abc: Affordance generalization beyond categories via semantic correspondence for robot manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Robo- abc: Affordance generalization beyond categories via semantic correspondence for robot manipulation

Reference 32

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Observation b20230e8-1212-4afc-98e1-6eaae80e4f72 · outbound

This paper cites DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-07-01T23:36:22.828889Z

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Observation 60d3fce1-f7b2-4102-b77c-ee077116fd34 · outbound

This paper cites Shamma, Michael S.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Shamma, Michael S

Reference 34

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Observation 7585ac92-ddb9-4a0b-92e0-a6fa7513d185 · outbound

This paper cites RAM: Retrieval-based affordance transfer for generalizable zero- shot robotic manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding RAM: Retrieval-based affordance transfer for generalizable zero- shot robotic manipulation

Reference 35

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Observation 35b063bb-d160-4e3c-ac40-7320c4f314d7 · outbound

This paper cites LISA: Reasoning segmentation via large language model.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding LISA: Reasoning segmentation via large language model

Reference 36

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Observation cde317c0-4b3a-4982-95e2-ce952193be1e · outbound

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

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Locate: Localize and transfer object parts for weakly supervised affordance grounding

Reference 37

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Observation de3aa980-aed5-4ee8-830d-5b4f57fd50da · outbound

This paper cites Learning precise affordances from egocentric videos for robotic manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Learning precise affordances from egocentric videos for robotic manipulation

Reference 38

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Observation 71197256-1c93-4ef3-b7a4-b18cbec1af63 · outbound

This paper cites In: Proceedings of the Asian Conference on Computer Vision (ACCV), pp.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding In: Proceedings of the Asian Conference on Computer Vision (ACCV), pp

Reference 39

Resolution: metadata mismatch; doi, observed 2026-06-28T14:22:18.490422Z

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Observation c879b5a2-9a08-47c4-b9ea-1512a6b51f85 · outbound

This paper cites Emogen: Emotional image content generation with text-to-image diffusion models.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Emogen: Emotional image content generation with text-to-image diffusion models

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T14:22:18.481547Z

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Observation d5507821-5415-4ea0-abb3-e0c4e5d51b07 · outbound

This paper cites Depth Anything 3: Recovering the Visual Space from Any Views.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Depth Anything 3: Recovering the Visual Space from Any Views

Reference 41

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T23:36:22.807886Z

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Observation 97c3a75c-1ab7-409b-8230-72376054f69a · outbound

This paper cites Fast interactive object annotation with Curve-GCN.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Fast interactive object annotation with Curve-GCN

Reference 42

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Observation 5ed72147-70d0-4324-905a-8f073c066079 · outbound

This paper cites Joint hand motion and interaction hotspots prediction from egocentric videos.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Joint hand motion and interaction hotspots prediction from egocentric videos

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation bf58e3c5-f3bf-4a87-aef6-924fc7cd121c · outbound

This paper cites Dreher, T.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Dreher, T

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T14:22:18.492671Z

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Observation 4ef0dfac-1115-4c18-9783-9a3065b1a390 · outbound

This paper cites Geal: Generalizable 3d affordance learning with cross-modal consistency.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Geal: Generalizable 3d affordance learning with cross-modal consistency

Reference 45

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation fd4277b8-c910-4da9-9612-6458b1721e61 · outbound

This paper cites Learning affordance grounding from exocentric images.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Learning affordance grounding from exocentric images

Reference 46

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Observation 1caec5dd-d1a3-46ca-95a3-689d467b8ccf · outbound

This paper cites GLOVER++: Unleashing the potential of affordance learning from human behaviors for robotic manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding GLOVER++: Unleashing the potential of affordance learning from human behaviors for robotic manipulation

Reference 47

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Observation 3010b5d4-154b-491a-8f44-5bba5e95651f · outbound

This paper cites Vagnet: Grounding 3d affordance from human-object interactions in videos, 2026.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Vagnet: Grounding 3d affordance from human-object interactions in videos, 2026

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:36:22.820296Z

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Observation 92d65551-31b3-4d85-be2e-cd8f808635f0 · outbound

This paper cites CALVIN: A benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks.IEEE Robotics and Automation Letters (RA-L), 7(3):7327–7334, 2022.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding CALVIN: A benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks.IEEE Robotics and Automation Letters (RA-L), 7(3):7327–7334, 2022

Reference 49

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Observation 048b27ac-2891-4227-80c4-b3fd6c98e3a1 · outbound

This paper cites SAM 3: Segment Anything with Concepts.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding SAM 3: Segment Anything with Concepts

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-07-01T23:36:22.824728Z

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Observation 3312bc5c-0aee-49dc-8cc2-e97d484f45a9 · outbound

This paper cites Scalable vision-language-action model pretraining for robotic manipulation with real-life human activity videos.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Scalable vision-language-action model pretraining for robotic manipulation with real-life human activity videos

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:36:22.803837Z

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Observation 1d7be398-421d-44e7-96e6-b43676e6d6c1 · outbound

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

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Where2act: From pixels to actions for articulated 3d objects

Reference 52

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Observation 2c3be21e-af25-4028-b1d9-a6fabf4e39de · outbound

This paper cites Teo, Cornelia Fermüller, and Yiannis Aloimonos.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Teo, Cornelia Fermüller, and Yiannis Aloimonos

Reference 53

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Observation 900a96f3-6c93-427d-857d-4483028b4381 · outbound

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

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Object-based affordances detection with convolutional neural networks and dense conditional random fields

Reference 55

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Observation c82a9a56-fb21-4e60-8107-7df41ca6aac7 · outbound

This paper cites Open-vocabulary affordance detection in 3D point clouds.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Open-vocabulary affordance detection in 3D point clouds

Reference 56

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Observation 69df2011-af0e-49ae-b425-9b43c00c53bd · outbound

This paper cites Transfer between Modalities with MetaQueries.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Transfer between Modalities with MetaQueries

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-07-01T23:36:22.799196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b6c6613c-7d80-4ac1-8753-fae39cfebc5c · outbound

This paper cites In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Work- shops (CVPR W), pp.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Work- shops (CVPR W), pp

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Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T14:22:18.465381Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c94a7f06-da94-4082-a90a-e2b72a9aa2c2 · outbound

This paper cites ToolFlowNet: Robotic manipulation with tools via predicting tool flow from point clouds.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding ToolFlowNet: Robotic manipulation with tools via predicting tool flow from point clouds

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation a02911ae-b33c-40a5-91ed-6521e94c37eb · outbound

This paper cites GREAT: Geometry-intention collaborative inference for open-vocabulary 3D object affordance grounding.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding GREAT: Geometry-intention collaborative inference for open-vocabulary 3D object affordance grounding

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation 0af11e42-42cf-4807-93a1-8a96f631da30 · outbound

This paper cites Artigrasp: Physically plausible synthesis of bi-manual dexterous grasping and articulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Artigrasp: Physically plausible synthesis of bi-manual dexterous grasping and articulation

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Resolution: verified exact; arxiv_id, observed 2026-06-28T14:22:18.467832Z

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Observation 80801a20-7ae6-4bff-b852-fda375e31351 · outbound

This paper cites Masked depth modeling for spatial perception.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Masked depth modeling for spatial perception

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Resolution: verified exact; arxiv_id, observed 2026-07-01T23:36:22.789518Z

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Observation 1eb87308-d814-443f-b4b8-b8cadf2f25b8 · outbound

This paper cites UAD: Unsupervised affordance distillation for generalization in robotic manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding UAD: Unsupervised affordance distillation for generalization in robotic manipulation

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Source-reported events for the cited work

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Observation d62cfb8e-7be6-4650-a11c-9a9912f24ca1 · outbound

This paper cites Roboafford: A dataset and benchmark for enhancing object and spatial affordance learning in robot ma- nipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Roboafford: A dataset and benchmark for enhancing object and spatial affordance learning in robot ma- nipulation

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation 118a1305-632e-4ee2-a499-a5ae89e2ba21 · outbound

This paper cites https://doi.org/10.1109/iros60139.2025.11247690.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding https://doi.org/10.1109/iros60139.2025.11247690

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Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T14:22:18.470390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8990a3a5-88f6-4717-b2cd-77fe2b176a9c · outbound

This paper cites Qwen3.5: Accelerating productivity with native multimodal agents, February.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Qwen3.5: Accelerating productivity with native multimodal agents, February

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation 6aafcae2-65c4-4f4a-bb64-368aa81726db · outbound

This paper cites an unresolved cited work.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Unresolved cited work

Reference 67

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation f8a25014-d56e-46d1-9c8e-d93d14b178c2 · outbound

This paper cites O3afford: One-shot 3d object-to-object affordance grounding for generalizable robotic manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding O3afford: One-shot 3d object-to-object affordance grounding for generalizable robotic manipulation

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation 9d7af56f-26af-4583-91b6-afeb86f56f67 · outbound

This paper cites InstructPart: Task-oriented part segmentation with instruction reasoning.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding InstructPart: Task-oriented part segmentation with instruction reasoning

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation a11224da-484a-414a-af79-d007ac2ad1c0 · outbound

This paper cites Videoafford: Grounding 3d affordance from human-object-interaction videos via multimodal large language model,.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Videoafford: Grounding 3d affordance from human-object-interaction videos via multimodal large language model,

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation e3086738-1ad5-4e75-ab10-9ee35fa83066 · outbound

This paper cites Videoafford: Grounding 3d affordance from human-object-interaction videos via multimodal large language model.arXiv preprint arXiv:2602.09638.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Videoafford: Grounding 3d affordance from human-object-interaction videos via multimodal large language model.arXiv preprint arXiv:2602.09638

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Resolution: verified exact; arxiv_id, observed 2026-07-01T23:36:22.845970Z

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Observation 2f1a8842-1303-4c3b-a32b-46124a3fa884 · outbound

This paper cites Affordance-R1: Reinforcement learning for generalizable affordance reasoning in multimodal large language models.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Affordance-R1: Reinforcement learning for generalizable affordance reasoning in multimodal large language models

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation 3b404c43-8f90-4b51-8867-e7255c9cd350 · outbound

This paper cites AffordBot: 3D fine-grained embodied reasoning via multimodal large language models.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding AffordBot: 3D fine-grained embodied reasoning via multimodal large language models

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation 11f12107-89d7-4364-9e0f-41279f7801e6 · outbound

This paper cites AffordDexGrasp: Open-set language-guided dexterous grasp with generalizable- instructive affordance.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding AffordDexGrasp: Open-set language-guided dexterous grasp with generalizable- instructive affordance

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation 1fac1db1-1a33-48c4-b2b0-989988b35494 · outbound

This paper cites RAGNet: Large-scale reasoning-based affordance segmentation benchmark towards general grasping.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding RAGNet: Large-scale reasoning-based affordance segmentation benchmark towards general grasping

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation 517545ad-2d3b-4849-a79b-fc43e9662fc4 · outbound

This paper cites RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation

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Resolution: verified exact; local_arxiv, observed 2026-07-01T23:36:22.816063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cc6dfeda-ed68-4b1b-b48b-e6dfa04b9eeb · outbound

This paper cites V AT-mart: Learning visual action trajectory proposals for manipulating 3d ARTiculated objects.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding V AT-mart: Learning visual action trajectory proposals for manipulating 3d ARTiculated objects

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation 5423649f-c035-4047-88e7-8b3ee0365713 · outbound

This paper cites AffordDP: Generalizable diffusion policy with transferable affordance.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding AffordDP: Generalizable diffusion policy with transferable affordance

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation ef578bc8-e0f2-45c8-8c21-40e9b475adc7 · outbound

This paper cites Sonata: Self-supervised learning of reliable point representations.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Sonata: Self-supervised learning of reliable point representations

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation 6b8ff5fc-0e9c-4e2f-87eb-b59d5c8f1eb4 · outbound

This paper cites Weakly-supervised affordance grounding guided by part-level semantic priors.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Weakly-supervised affordance grounding guided by part-level semantic priors

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation 542e2fe9-e8e2-4eb4-8788-2f1a40e4a90c · outbound

This paper cites A0: An affordance-aware hierarchical model for general robotic manipulation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding A0: An affordance-aware hierarchical model for general robotic manipulation

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Source-reported events for the cited work

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Observation 71474842-ff33-433d-afcf-eea34903129c · outbound

This paper cites Ground- ing 3d object affordance from 2d interactions in images.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Ground- ing 3d object affordance from 2d interactions in images

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation 1f2584b3-592c-486b-a639-4a29d283d196 · outbound

This paper cites DFormerv2: Geometry self-attention for RGBD semantic segmentation.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding DFormerv2: Geometry self-attention for RGBD semantic segmentation

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation d0bc9dc8-e4d6-4131-b18a-633afe26781d · outbound

This paper cites Yoshida, S.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Yoshida, S

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Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T14:22:18.460485Z

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Observation fbc28354-bace-4bd9-bef0-e2dccb5d4114 · outbound

This paper cites Text-driven affordance learning from egocentric vision.Adv.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Text-driven affordance learning from egocentric vision.Adv

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Resolution: verified exact; arxiv_id, observed 2026-06-28T14:22:18.462979Z

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Observation 6ea6d13a-e687-42ea-b371-5a773c581d1d · outbound

This paper cites Generating 6DoF object manipulation trajectories from action description in egocentric vision.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Generating 6DoF object manipulation trajectories from action description in egocentric vision

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation 0723ec1d-2b07-45fd-85b7-ed887080e07e · outbound

This paper cites SeqAfford: Sequential 3D affordance reasoning via multimodal large language model.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding SeqAfford: Sequential 3D affordance reasoning via multimodal large language model

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation 3a92ccce-40be-4509-a916-55595c0928e2 · outbound

This paper cites In: 2025 IEEE International Conference on Robotics and Automation (ICRA), pp.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding In: 2025 IEEE International Conference on Robotics and Automation (ICRA), pp

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Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T14:22:18.456202Z

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Observation 6226e9fb-ac16-436e-a4aa-b6293ad66b52 · outbound

This paper cites General flow as foundation affordance for scalable robot learning.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding General flow as foundation affordance for scalable robot learning

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation 59efab5a-732f-4a88-8e40-3af054875e5e · outbound

This paper cites RoboPoint: A vision-language model for spatial affordance prediction in robotics.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding RoboPoint: A vision-language model for spatial affordance prediction in robotics

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Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

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Observation 9de7e863-6ba0-4085-839b-23edeab5e173 · outbound

This paper cites an unresolved cited work.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Unresolved cited work

Reference 91

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21cab0bf-824c-45f7-99be-ac51bd7e5177 · outbound

This paper cites FlowBot++: Learning generalized articulated objects manipulation via articulation projection.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding FlowBot++: Learning generalized articulated objects manipulation via articulation projection

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Source-reported events for the cited work

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Observation 0ed549d5-1ebb-42d1-9e79-6fcec185634c · outbound

This paper cites Affordance-guided robotic grasping via multimodal large language model reasoning.IEEE Trans Autom.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Affordance-guided robotic grasping via multimodal large language model reasoning.IEEE Trans Autom

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Resolution: verified exact; arxiv_id, observed 2026-06-28T14:22:18.495053Z

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Observation 443ef74d-b1d0-4435-8120-7ab8a6fb8538 · outbound

This paper cites Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment

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Resolution: malformed identifier; doi_truncated, observed 2026-06-28T14:22:18.458049Z

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Observation 011e6fc3-d562-42b7-863d-14f281a90352 · outbound

This paper cites Freeman, Frédo Durand, Eli Shechtman, and Xun Huang.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Freeman, Frédo Durand, Eli Shechtman, and Xun Huang

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Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T14:22:18.453652Z

Source-reported events for the cited work

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Observation 6b22beb0-3fae-48fd-bb30-2ccd60f49834 · outbound

This paper cites an unresolved cited work.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Unresolved cited work

Reference 97

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Observation aed7fd1d-250f-4c01-a751-d22773f7126e · outbound

This paper cites an unresolved cited work.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Unresolved cited work

Reference 98

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Unavailable: canonical work link unavailable.

Observation 0b17b6a4-20a1-450a-a7bb-35dd61bfdc70 · outbound

This paper cites Use ‘obs_frame‘ to phrase it in visible terms.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding Use ‘obs_frame‘ to phrase it in visible terms

Reference 99

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd62c4e0-e04e-40ed-badf-cc6f342812ae · outbound

This paper cites top-left.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding top-left

Reference 100

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Unavailable: canonical work link unavailable.

Observation 26de986d-5749-4054-953d-6021014fb70b · outbound

This paper cites 21 If still ambiguous, choose the most likely minimal part and add one discriminative qualifier (e.g., color/position).

AFUN: Towards an Affordance Foundation Model for Functionality Understanding 21 If still ambiguous, choose the most likely minimal part and add one discriminative qualifier (e.g., color/position)

Reference 101

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Unavailable: canonical work link unavailable.

Observation 2dc573b1-21e6-4fec-8826-2d9776b7b00e · outbound

This paper cites it", "that.

AFUN: Towards an Affordance Foundation Model for Functionality Understanding it", "that

Reference 102

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 023d3b32-f738-4ef1-8d7b-e13203a5cf8c · outbound

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AFUN: Towards an Affordance Foundation Model for Functionality Understanding robot",

Reference 103

Resolution: unresolved; no resolver link, observed 2026-06-28T14:13:13.043886Z

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Outbound references

Pith citing papers