Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T10:32:25.265609Z
Paper Citation Record · LEDGER
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping
As of 18 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 0 inbound Pith citation observations for arXiv:2507.23734.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
75 of 75 outbound references displayed
- verified exact0
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- unresolved20
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a02b68eb-28f2-4cf0-94d8-9edce78dfcf0 · outbound
This paper cites CVGIP: Image Understanding, 1994.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping CVGIP: Image Understanding, 1994
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d187644f-1afb-447b-b459-7f038b942b02 · outbound
This paper cites GPT-4 Technical Report.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping GPT-4 Technical Report
Reference 2
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8720acd0-0d0b-4fe0-b3b9-0345da2cdae8 · outbound
This paper cites Affordances from human videos as a versa- tile representation for robotics.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Affordances from human videos as a versa- tile representation for robotics
Reference 3
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c46679f7-37f1-4b2d-8ed0-7af06408f937 · outbound
This paper cites RT-1: Robotics Transformer for Real-World Control at Scale.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping RT-1: Robotics Transformer for Real-World Control at Scale
Reference 4
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7799735-52f9-4122-ab32-7c17f39395c6 · outbound
This paper cites Coco- stuff: Thing and stuff classes in context.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Coco- stuff: Thing and stuff classes in context
Reference 5
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0e8e39ce-4141-4ecf-b16f-06eb77082bc7 · outbound
This paper cites Affordance grounding from demonstration video to target image.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Affordance grounding from demonstration video to target image
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.196815Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0ef1dfe8-774a-4398-a427-9b9917c01ab4 · outbound
This paper cites Learning to act properly: Predicting and explaining affordances from images.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Learning to act properly: Predicting and explaining affordances from images
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.186795Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6aa0fa14-1dd6-41f8-a0df-7d9dab3504ee · outbound
This paper cites Rescaling egocentric vision: Collection, pipeline and chal- lenges for epic-kitchens-100.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Rescaling egocentric vision: Collection, pipeline and chal- lenges for epic-kitchens-100
Reference 8
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 91a25caa-4faf-4968-9885-bf71bb8a718b · outbound
This paper cites Affordancenet: An end-to-end deep learning approach for object affordance detection.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Affordancenet: An end-to-end deep learning approach for object affordance detection
Reference 9
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 10e9dc6e-2c4d-4067-8a3c-a3a265093bc6 · outbound
This paper cites Graspnet-1billion: A large-scale benchmark for general ob- ject grasping.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Graspnet-1billion: A large-scale benchmark for general ob- ject grasping
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.154261Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ea9c919c-b587-4039-b4af-4734de01b46e · outbound
This paper cites Demo2vec: Reasoning object affordances from online videos.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Demo2vec: Reasoning object affordances from online videos
Reference 11
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation aac59ffe-8c51-4dbe-b93e-5e02469ed539 · outbound
This paper cites Learning visual at- tributes.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Learning visual at- tributes
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.134036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b87b34b5-650e-44d3-84fb-d411ecd1ce3e · outbound
This paper cites The ecological approach to visual percep- tion: classic edition.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping The ecological approach to visual percep- tion: classic edition
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.122442Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1d7241cb-b9aa-4747-b7cb-a1aacc2d60eb · outbound
This paper cites Ego4d: Around the world in 3,000 hours of egocentric video.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Ego4d: Around the world in 3,000 hours of egocentric video
Reference 14
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 51891693-5bda-4954-bcce-31ebe8202c7e · outbound
This paper cites HAN- DAL: A dataset of real-world manipulable object categories with pose annotations, affordances, and reconstructions.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping HAN- DAL: A dataset of real-world manipulable object categories with pose annotations, affordances, and reconstructions
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.105164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 45d50d61-3d24-4638-9b05-db7e36b8d77a · outbound
This paper cites CoPa: General Robotic Manipulation through Spatial Constraints of Parts with Foundation Models.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping CoPa: General Robotic Manipulation through Spatial Constraints of Parts with Foundation Models
Reference 16
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4af09ab1-1fb9-4458-9ea9-0377dd732ca7 · outbound
This paper cites Manipvqa: Injecting robotic affordance and physi- cally grounded information into multi-modal large language models.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Manipvqa: Injecting robotic affordance and physi- cally grounded information into multi-modal large language models
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.092413Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d6ccc560-4906-4dbd-8ab5-a2aa4e7525e8 · outbound
This paper cites VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models
Reference 18
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2f7e2719-cc25-4c0a-8b16-d3cf56fb6074 · outbound
This paper cites ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation
Reference 19
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b1d949f-8485-4f81-a073-d20afbfb7f4e · outbound
This paper cites Rlbench: The robot learning benchmark & learning environment.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Rlbench: The robot learning benchmark & learning environment
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.081647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3a14c29d-4e7b-4c70-993c-63b4b4b12836 · outbound
This paper cites Affordpose: A large-scale dataset of hand-object inter- actions with affordance-driven hand pose.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Affordpose: A large-scale dataset of hand-object inter- actions with affordance-driven hand pose
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.070722Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1253d0a1-8580-42d6-9e89-9af3567d52e9 · outbound
This paper cites Robo-abc: Affordance gener- alization beyond categories via semantic correspondence for robot manipulation.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Robo-abc: Affordance gener- alization beyond categories via semantic correspondence for robot manipulation
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.059227Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1588e184-39ef-4389-ac41-c46cd934ad2a · outbound
This paper cites Hotr: End-to-end human-object in- teraction detection with transformers.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Hotr: End-to-end human-object in- teraction detection with transformers
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.049176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 24b0e37e-5ef0-4fce-99b6-d89630266b2e · outbound
This paper cites Segment any- thing.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Segment any- thing
Reference 24
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aebd61c6-f6b9-4881-b66f-62753f1aeaff · outbound
This paper cites Vi- sual object-action recognition: Inferring object affordances from human demonstration.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Vi- sual object-action recognition: Inferring object affordances from human demonstration
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.032562Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 23f00b6e-7c49-48e5-84e9-10594eda234a · outbound
This paper cites Lisa: Reasoning segmenta- tion via large language model.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Lisa: Reasoning segmenta- tion via large language model
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.022085Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 144793f5-cdf2-4fa2-862d-df829fef8975 · outbound
This paper cites Locate: Localize and transfer object parts for weakly super- vised affordance grounding.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Locate: Localize and transfer object parts for weakly super- vised affordance grounding
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.012107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2aa01f02-946a-4388-905d-952bbc413809 · outbound
This paper cites One-shot open affordance learning with foundation models.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping One-shot open affordance learning with foundation models
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:26.001822Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 09d4aba9-02c8-4492-8209-a85854879003 · outbound
This paper cites Learning precise affordances from egocentric videos for robotic manipulation.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Learning precise affordances from egocentric videos for robotic manipulation
Reference 29
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bec58670-f871-4476-8703-3b5a6113d74d · outbound
This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
Reference 30
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7ca354fd-8c01-4c93-9a21-92c49b5b7cda · outbound
This paper cites Manipllm: Embodied multimodal large language model for object-centric robotic manipulation.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Manipllm: Embodied multimodal large language model for object-centric robotic manipulation
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.985386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6133e498-05ae-4c96-b1d6-429adfa140ec · outbound
This paper cites Laso: Language-guided affordance seg- mentation on 3d object.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Laso: Language-guided affordance seg- mentation on 3d object
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.974938Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4df390e5-78e8-485f-bd93-ddf41488db7c · outbound
This paper cites Visual instruction tuning.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Visual instruction tuning
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.964107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 19797398-38b1-4ae3-aa04-539d6da20382 · outbound
This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
Reference 34
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ee7e54e-15cd-46a6-bd93-3cf5669690cb · outbound
This paper cites Learning to seg- ment affordances.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Learning to seg- ment affordances
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.954245Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a7ac2acf-266d-4169-b105-1550ed1a4235 · outbound
This paper cites Learning affordance grounding from exocen- tric images.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Learning affordance grounding from exocen- tric images
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.944380Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a5ceb89e-aead-4875-957a-a69e42158963 · outbound
This paper cites Leverage interactive affinity for affordance learning.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Leverage interactive affinity for affordance learning
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.933636Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 438f2bb6-153c-4a54-8792-57f71238ec99 · outbound
This paper cites Affordance detection of tool parts from geomet- ric features.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Affordance detection of tool parts from geomet- ric features
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.923936Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 63494fdd-680f-4243-a7d3-231435e93d5c · outbound
This paper cites PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:32:25.133699Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 279df1e3-c08e-44ad-bbb4-b792577dbaa6 · outbound
This paper cites Object-based affordances detection with convolutional neural networks and dense conditional random fields.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Object-based affordances detection with convolutional neural networks and dense conditional random fields
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.913098Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fe60effd-845e-43db-8772-d8a66a868c31 · outbound
This paper cites LLARVA: Vision-Action Instruction Tuning Enhances Robot Learning.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping LLARVA: Vision-Action Instruction Tuning Enhances Robot Learning
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:32:25.140850Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 568dbc66-6958-43a2-8310-8d5b8bb39810 · outbound
This paper cites Open X-Embodiment: Robotic Learning Datasets and RT-X Models.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:32:25.144626Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9395c8a7-eba0-46aa-8f62-39ffcdcc682d · outbound
This paper cites Understanding 3d object interaction from a single image.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Understanding 3d object interaction from a single image
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.903015Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4e37ce8d-e4e4-43ff-a16a-000c9eabf540 · outbound
This paper cites Understanding 3d object articulation in in- ternet videos.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Understanding 3d object articulation in in- ternet videos
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.893593Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3acbcdc1-cde4-4f33-a530-eae700447603 · outbound
This paper cites Affordancellm: Grounding affordance from vision language models.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Affordancellm: Grounding affordance from vision language models
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.884120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 07afc8be-be07-43f7-8b6f-c873077d85a9 · outbound
This paper cites Learn- ing transferable visual models from natural language super- vision.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Learn- ing transferable visual models from natural language super- vision
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.873987Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e0bda9f1-999f-44c5-b844-0d1e09efd187 · outbound
This paper cites Paco: Parts and attributes of common objects.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Paco: Parts and attributes of common objects
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.863589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7bbee5cf-1750-4dba-9586-c234fd8b1aa5 · outbound
This paper cites Glamm: Pixel grounding large multimodal model.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Glamm: Pixel grounding large multimodal model
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.852279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 584188ec-1f8a-464e-ac32-01468952ad28 · outbound
This paper cites Language embedded radiance fields for zero-shot task- oriented grasping.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Language embedded radiance fields for zero-shot task- oriented grasping
Reference 49
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 25e4037f-77db-4d79-824d-c37fcbfdb0c9 · outbound
This paper cites SAM 2: Segment Anything in Images and Videos.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping SAM 2: Segment Anything in Images and Videos
Reference 50
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 718e2134-abb3-4c9b-a156-ee6595465e74 · outbound
This paper cites Weakly supervised affordance detection.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Weakly supervised affordance detection
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.828815Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1c771262-5fa2-4d44-a6e2-29826796ef8b · outbound
This paper cites Understanding human hands in contact at internet scale.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Understanding human hands in contact at internet scale
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.817689Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a0042570-37b1-472e-a294-4bcef064b000 · outbound
This paper cites Cliport: What and where pathways for robotic manipulation.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Cliport: What and where pathways for robotic manipulation
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.807772Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 977a0ac7-ec82-4179-89d8-0477a0c27e72 · outbound
This paper cites Going denser with open-vocabulary part segmentation.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Going denser with open-vocabulary part segmentation
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.796734Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d3e103d5-bcd7-4c99-a586-9ac318fe8d39 · outbound
This paper cites Grasp-Anything: Large-scale Grasp Dataset from Foundation Models.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Grasp-Anything: Large-scale Grasp Dataset from Foundation Models
Reference 55
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 76cc7cad-e7f0-40d9-bd88-5773ab40ca61 · outbound
This paper cites Language- driven grasp detection.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Language- driven grasp detection
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.786244Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 84142094-1128-4c11-8447-a3a775c5d7da · outbound
This paper cites Bridgedata v2: A dataset for robot learning at scale.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Bridgedata v2: A dataset for robot learning at scale
Reference 57
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation cb04d872-397e-4752-8ce4-ab11148848da · outbound
This paper cites An interactive navigation method with effect-oriented affordance.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping An interactive navigation method with effect-oriented affordance
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.764209Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 430feffa-065c-4c9b-8f0e-fc368e294184 · outbound
This paper cites Move as you say interact as you can: Language-guided human motion generation with scene af- fordance.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Move as you say interact as you can: Language-guided human motion generation with scene af- fordance
Reference 59
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6ded240c-6307-461b-911b-379849cab36e · outbound
This paper cites Florence-2: Advancing a unified representation for a variety of vision tasks.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Florence-2: Advancing a unified representation for a variety of vision tasks
Reference 60
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 48e361dc-13ac-4eb4-9af4-1dde956d0a3e · outbound
This paper cites NaturalVLM: Leveraging Fine-grained Natural Language for Affordance-Guided Visual Manipulation.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping NaturalVLM: Leveraging Fine-grained Natural Language for Affordance-Guided Visual Manipulation
Reference 61
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6fd9515a-789e-4f06-91a7-b9eac5633680 · outbound
This paper cites Grounding 3d object affordance from 2d interactions in images.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Grounding 3d object affordance from 2d interactions in images
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.722125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fd875b95-6f7f-4c19-8b97-e59157976fe8 · outbound
This paper cites Modeling context in referring expres- sions.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Modeling context in referring expres- sions
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.709820Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b43e9e2e-8617-4ae6-b1c1-9fa09be7c6ca · outbound
This paper cites UniAff: A Unified Representation of Affordances for Tool Usage and Articulation with Vision-Language Models.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping UniAff: A Unified Representation of Affordances for Tool Usage and Articulation with Vision-Language Models
Reference 64
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd42b3fd-f426-48a5-8c7c-fe4fad2b5cc2 · outbound
This paper cites Taskonomy: Disentangling task transfer learning.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Taskonomy: Disentangling task transfer learning
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.696790Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation efa61ad4-1320-4d33-a425-b8b343d0dc64 · outbound
This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Judging llm-as-a-judge with mt-bench and chatbot arena
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.684104Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 908f6593-54d2-4814-b086-31e55539e572 · outbound
This paper cites Scene parsing through ade20k dataset.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Scene parsing through ade20k dataset
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.671655Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation da2d1f98-7288-4761-b2af-0e39b6c1512c · outbound
This paper cites Egoobjects: A large-scale egocentric dataset for fine-grained object understanding.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Egoobjects: A large-scale egocentric dataset for fine-grained object understanding
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.658413Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 649ca24c-a3bc-48e7-bda9-6e26e480a93c · outbound
This paper cites From these data, we emphasize grasping-oriented objects, encompassing both those with handles and those without.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping From these data, we emphasize grasping-oriented objects, encompassing both those with handles and those without
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.644075Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a7e76a73-f737-4c2f-b2d3-05c9915bce55 · outbound
This paper cites an unresolved cited work.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Unresolved cited work
Reference 70
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 305189ae-052a-42fd-9e34-549aeea51b18 · outbound
This paper cites microwave, open the door.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping microwave, open the door
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.615905Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 08782851-4fed-45ef-a084-bde80db069e1 · outbound
This paper cites an unresolved cited work.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Unresolved cited work
Reference 72
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0606ba0a-5fc7-4ce7-9d21-425cba0712f9 · outbound
This paper cites an unresolved cited work.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Unresolved cited work
Reference 73
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T10:32:25.588451Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6170e9ec-c643-47b9-b4ca-a470aaff50e0 · outbound
This paper cites Open the top drawer.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping Open the top drawer
Reference 74
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.575152Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ed650da2-27aa-4526-a340-876a65596280 · outbound
This paper cites open the top drawer,.
RAGNet: Large-scale Reasoning-based Affordance Segmentation Benchmark towards General Grasping open the top drawer,
Reference 75
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T10:32:25.553855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
No inbound Pith citation observations are available.