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Paper Citation Record · LEDGER

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

As of 8 August 2026, this Paper Citation Record lists 100 of 104 outbound references and 10 inbound Pith citation observations for arXiv:2502.08643.

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

pith.paper-citation-record.v1
2502.08643 v2

Coverage vector

measured 100 of 104 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T00:03:16.780089Z

measured 110 of 110 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:57:29.723051Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T06:37:07.457138Z

Reference resolution

100 of 104 outbound references displayed

  • verified exact3
  • verified fuzzy8
  • unresolved89
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6b1266be-45f8-4784-acdc-680306b1aa09 · outbound

This paper cites Gpt-4 technical report,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Gpt-4 technical report,

Reference 1

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source=pdf_text observed=2026-08-08T00:03:16.267564Z digest=sha256:85b419d6eb24e680829391bd73f42a23ff6e68e64c7559501e0273978b908952

Observation 732a8927-91f6-4814-8659-efcd658a3d8c · outbound

This paper cites Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language

Reference 2

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source=pdf_text observed=2026-08-08T00:03:16.273920Z digest=sha256:79a3c1c8d04950e4c23f8250b7ae5265ff8920c88c7c5fa16846a761ba9a2f5a

Observation 5d8eb4fa-1ed6-41ac-914e-a9fbc19221b6 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Learning Transferable Visual Models From Natural Language Supervision

Reference 3

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source=pdf_text observed=2026-08-08T00:03:16.280094Z digest=sha256:f61a1dd96769c5e01c2a9eb39839d86952a9bdb7f33ae1b3be092e16042c078a

Observation ad5ac58d-c798-4e2d-a5c2-99094d62687f · outbound

This paper cites Scaling up visual and vision-language representation learning with noisy text supervision,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Scaling up visual and vision-language representation learning with noisy text supervision,

Reference 4

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source=pdf_text observed=2026-08-08T00:03:16.286143Z digest=sha256:ddb2afd14ca2db1973b0ca21abc6137574938f411fa1545a855b3c4dc2cbc212

Observation 317fed13-de3b-471c-b25a-0a71ef9299e6 · outbound

This paper cites Blip: Bootstrapping language- image pre-training for unified vision-language understanding and generation,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Blip: Bootstrapping language- image pre-training for unified vision-language understanding and generation,

Reference 5

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source=pdf_text observed=2026-08-08T00:03:16.297405Z digest=sha256:53aaadc958a60e928404d9a7d0d7118855b345c34aa7fa6aca6333a17c371c21

Observation 088d4fc6-afd0-42c9-93a8-351b6d7825e6 · outbound

This paper cites BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 6

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source=pdf_text observed=2026-08-08T00:03:16.303251Z digest=sha256:88a7f7b88e761d77d8dff5e6ec5366a7fb1eac472f0517e92eb88567c499b83a

Observation 142373a9-c858-4b13-9cd2-3eb74d7aae02 · outbound

This paper cites Flamingo: a Visual Language Model for Few-Shot Learning.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Flamingo: a Visual Language Model for Few-Shot Learning

Reference 7

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source=pdf_text observed=2026-08-08T00:03:16.308743Z digest=sha256:a46baad3e06d7ffdab4c8c73afc6bdbe2e2da87e6149fea5413fb7087245042a

Observation e8b24053-697c-4782-bd1c-3f03882285ba · outbound

This paper cites CoCa: Contrastive Captioners are Image-Text Foundation Models.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 8

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source=pdf_text observed=2026-08-08T00:03:16.314808Z digest=sha256:3326931cee1f49a1027bcd0e5e49f4bfc2b543456e9b2bfc7bd9d5c81835dd75

Observation d3f89353-8c84-41ef-ae3a-1584c3c226c8 · outbound

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

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation

Reference 9

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source=pdf_text observed=2026-08-08T00:03:16.320032Z digest=sha256:6345b9d66a21f5c5b6eb548dcf962a96010bec6da689ede78f24c53431719500

Observation e2920c4d-8d7c-4f4c-ad6a-f74eb3245b83 · outbound

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

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 10

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source=pdf_text observed=2026-08-08T00:03:16.324781Z digest=sha256:f8801c900a135defb92368ce1262a76c97fd79c22be27de90b49b2ca4c63b6ca

Observation 5b8a8ef4-3898-4eb1-8628-278a271f6414 · outbound

This paper cites Code as Policies: Language Model Programs for Embodied Control.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Code as Policies: Language Model Programs for Embodied Control

Reference 11

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source=pdf_text observed=2026-08-08T00:03:16.329340Z digest=sha256:ce465dff321800c08cecfe74baf7071ae8b796bbe024c68762b4ce2b980aa9f5

Observation 555d2eda-675a-4040-be29-929cfa91ba82 · outbound

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

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models

Reference 12

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source=pdf_text observed=2026-08-08T00:03:16.334277Z digest=sha256:6d498cd3c2f02cbfa9c7ca2cec4ff476d5b9c942b633a8bea6ec1a3d73d7cde7

Observation 662ae966-d8f8-442b-a4d3-1062143c9a09 · outbound

This paper cites RT-1: Robotics Transformer for Real-World Control at Scale.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards RT-1: Robotics Transformer for Real-World Control at Scale

Reference 13

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source=pdf_text observed=2026-08-08T00:03:16.339166Z digest=sha256:853c69c2dddfda1285d54ab5fee5ae2b4ee19590fdae6ed90be95c4d8f1c0f06

Observation 83199657-d3b9-4475-b670-f7445c5e3894 · outbound

This paper cites RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 14

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source=pdf_text observed=2026-08-08T00:03:16.344340Z digest=sha256:ec1613968ef4c20d20dc6fd8fb27cda7fc23a63830695c7b8d07fb15862ce92e

Observation 8892c62c-f0fb-4578-9e79-6e293228ce01 · outbound

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

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards MOKA: Open-World Robotic Manipulation through Mark-Based Visual Prompting

Reference 15

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source=pdf_text observed=2026-08-08T00:03:16.349095Z digest=sha256:ab243741ef5872c2af48d929dc8394f9771631b56a989700f84be38a773b880c

Observation 529ffc25-9927-46a7-a709-d8d606eb9dcb · outbound

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

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards CoPa: General Robotic Manipulation through Spatial Constraints of Parts with Foundation Models

Reference 16

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source=pdf_text observed=2026-08-08T00:03:16.353903Z digest=sha256:64f58a991b7fb933572448be45d106e546c3679390366729800f015aeb780143

Observation 7cfb61bf-3992-4246-8236-c50008ec1e4b · outbound

This paper cites Octo: An Open-Source Generalist Robot Policy.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Octo: An Open-Source Generalist Robot Policy

Reference 17

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source=pdf_text observed=2026-08-08T00:03:16.358600Z digest=sha256:de5d367f5ce0f27f8439fd33ea8ecc3f12c97627a552491b566f80ef6ccc9f0d

Observation 4373253c-8b85-4c23-9d85-3f86929dab2c · outbound

This paper cites Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model

Reference 18

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source=pdf_text observed=2026-08-08T00:03:16.363277Z digest=sha256:e6468ed2c8a2cf349df659f4973bc1b86137be0c71814a9143f0fd0847e39fc3

Observation b6a4f8a9-fda5-4db4-a2c9-3f87bb869704 · outbound

This paper cites Creative Robot Tool Use with Large Language Models.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Creative Robot Tool Use with Large Language Models

Reference 19

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source=pdf_text observed=2026-08-08T00:03:16.367942Z digest=sha256:eda763ba6bf3dfd58e076fc66110b61c00625b4983d060478cb2a2de06c46896

Observation 0653a99c-f2a4-4786-9ffe-584c89d177be · outbound

This paper cites Generalizable Long-Horizon Manipulations with Large Language Models.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Generalizable Long-Horizon Manipulations with Large Language Models

Reference 20

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source=pdf_text observed=2026-08-08T00:03:16.373020Z digest=sha256:ae77185e4b631fa8c54f42fcbc0af420f1818ec5e106d626b36c6075c6add728

Observation 5b4a0c47-36b8-4475-a554-5451989a4704 · outbound

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

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs

Reference 21

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source=pdf_text observed=2026-08-08T00:03:16.378325Z digest=sha256:135cfea1e64d0983463ceadbcfa82bc22365e62d5d90574dffbb61cc861a1665

Observation a83dc631-d7b4-4afe-ab66-230b13764f82 · outbound

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

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Keypoint Action Tokens Enable In-Context Imitation Learning in Robotics

Reference 22

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source=pdf_text observed=2026-08-08T00:03:16.383871Z digest=sha256:0003e67d3c6cd044101d8fa6a28dbc14269782c2c45ea2a718121e3f2a77a2e4

Observation ed59c352-b145-4bba-8d31-3040c9a2daa1 · outbound

This paper cites Large language models for robotics: A survey,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Large language models for robotics: A survey,

Reference 23

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source=pdf_text observed=2026-08-08T00:03:16.389090Z digest=sha256:4d27d222418a438f9e585194cee96ccc339b52fe35944efe9d3e77833c41a8b8

Observation d943c6f6-736e-4c43-85b7-6eefa4b85dc4 · outbound

This paper cites Distilling and retrieving generalizable knowledge for robot manipulation via language corrections,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Distilling and retrieving generalizable knowledge for robot manipulation via language corrections,

Reference 24

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source=pdf_text observed=2026-08-08T00:03:16.393865Z digest=sha256:f583bc3e9b9aa523563f228583867448406f40ce5967b302d9114586cbbf532b

Observation 19238c07-5158-45b6-b551-47101acad255 · outbound

This paper cites How to prompt your robot: A promptbook for manipulation skills with code as policies,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards How to prompt your robot: A promptbook for manipulation skills with code as policies,

Reference 25

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source=pdf_text observed=2026-08-08T00:03:16.398731Z digest=sha256:50199376dbb5afabc3b326e01e403121e36d7c432bc6bbcdd42f2829f843371d

Observation 3da5c2a2-ffd0-452c-9a01-2929b080cd96 · outbound

This paper cites Generative expressive robot behaviors using large language models,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Generative expressive robot behaviors using large language models,

Reference 26

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source=pdf_text observed=2026-08-08T00:03:16.403571Z digest=sha256:ce93ca4c69288c6aa17e8118a0da0f12f16fb6ccb62f8f0a19d84f83fc9c063c

Observation 664f3558-b44e-49a5-8a93-9ed2c2f2dadd · outbound

This paper cites Learning to Learn Faster from Human Feedback with Language Model Predictive Control.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Learning to Learn Faster from Human Feedback with Language Model Predictive Control

Reference 27

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.408366Z digest=sha256:8c7d31f14735b101cb6a13e323e016bdd6a9ac2a6d6047af4c37176da7044306

Observation 1f5651fc-e0eb-4dfe-99bd-811acf0b9be5 · outbound

This paper cites Grounded decoding: Guiding text generation with grounded models for embodied agents,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Grounded decoding: Guiding text generation with grounded models for embodied agents,

Reference 28

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source=pdf_text observed=2026-08-08T00:03:16.413592Z digest=sha256:b4c2e2000d86d90a45a4c00590e5f57e56d6026fd6a7efe4a2793664ac86230b

Observation f07379f8-3bc7-49e1-b5ee-ac82877c3989 · outbound

This paper cites Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners

Reference 29

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source=pdf_text observed=2026-08-08T00:03:16.418242Z digest=sha256:bc6a26931c6e41baf72cef89e31282f08d7e3a30eb409c3c708f60e3b383323e

Observation d8d02fa8-5955-4d62-a16b-aff96c21dac7 · outbound

This paper cites VIMA: General Robot Manipulation with Multimodal Prompts.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards VIMA: General Robot Manipulation with Multimodal Prompts

Reference 30

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source=pdf_text observed=2026-08-08T00:03:16.423650Z digest=sha256:f8681f0194adb4245ec450ed4b68c38636660500a9d2b036d08978c02683958e

Observation 2efc599c-5a43-49c0-8a75-ce0d06ab43bd · outbound

This paper cites Guiding Long-Horizon Task and Motion Planning with Vision Language Models.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Guiding Long-Horizon Task and Motion Planning with Vision Language Models

Reference 31

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source=pdf_text observed=2026-08-08T00:03:16.429020Z digest=sha256:a10a49ea418f6e6f223f2e6c0cc5039f7c5fc4eaffaf54d3d55ab194b2132929

Observation 96103a68-ba73-4019-9b32-e39a14f13af7 · outbound

This paper cites AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation

Reference 32

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source=pdf_text observed=2026-08-08T00:03:16.434203Z digest=sha256:405eaa0307b03986ef23c6f7b86cfdfb6a13af678b4c3b810d3290fcb6336f14

Observation 44dc6a78-0b65-48c8-bf06-bc23b98a7823 · outbound

This paper cites Manipulate-Anything: Automating Real-World Robots using Vision-Language Models.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Manipulate-Anything: Automating Real-World Robots using Vision-Language Models

Reference 33

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source=pdf_text observed=2026-08-08T00:03:16.439194Z digest=sha256:549709567c5157fa3d5b9da083e76a33842a767a324d3e7ae2567d99ad38a8f7

Observation 8ea0237c-f5f4-453d-96ec-09e0aa7d84b6 · outbound

This paper cites RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Robotics.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Robotics

Reference 34

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source=pdf_text observed=2026-08-08T00:03:16.443621Z digest=sha256:4f0cb48318e1599f08413838bd7fd98df3dab20d96e6d181b5d5fa12d94a71e6

Observation 58b5b6b3-2faf-4a72-b4b4-41e25a9211d5 · outbound

This paper cites Progprompt: program genera- tion for situated robot task planning using large language models,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Progprompt: program genera- tion for situated robot task planning using large language models,

Reference 35

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Observation 007f0ff7-ce39-4135-9000-08b40544ad0a · outbound

This paper cites KALIE: Fine-Tuning Vision-Language Models for Open-World Manipulation without Robot Data.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards KALIE: Fine-Tuning Vision-Language Models for Open-World Manipulation without Robot Data

Reference 36

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Observation 99f53cd6-4de4-4efb-a43d-0f792ba826d3 · outbound

This paper cites Eurekaverse: Environment Curriculum Generation via Large Language Models.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Eurekaverse: Environment Curriculum Generation via Large Language Models

Reference 37

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source=pdf_text observed=2026-08-08T00:03:16.457081Z digest=sha256:1d3d341a37f3204ce69dd04f43b0ad45db7c55f3d4d04068d1dd23bcd1949ae0

Observation 15488d81-4889-416c-84ba-099316a576f3 · outbound

This paper cites Robotic Control via Embodied Chain-of-Thought Reasoning.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Robotic Control via Embodied Chain-of-Thought Reasoning

Reference 38

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Observation 5ed50014-dc07-4ba7-9b2c-2fb866fddf9a · outbound

This paper cites Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Reference 39

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source=pdf_text observed=2026-08-08T00:03:16.466863Z digest=sha256:a2a7b7a77aaef2694306e81538969220f08de5638a02a96c88b2c4df84e0282e

Observation 4394fe00-d420-4333-a55f-b6681f54234c · outbound

This paper cites Language models as zero-shot planners: Extracting actionable knowledge for embodied agents,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Language models as zero-shot planners: Extracting actionable knowledge for embodied agents,

Reference 40

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source=pdf_text observed=2026-08-08T00:03:16.471416Z digest=sha256:ebe602427bc900e44c17e479d1e739cd5257adefb6dfdbe7dddb3f46f784098d

Observation 33f15191-450c-470f-9b63-ab03f410c084 · outbound

This paper cites RT-H: Action Hierarchies Using Language.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards RT-H: Action Hierarchies Using Language

Reference 41

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source=pdf_text observed=2026-08-08T00:03:16.475851Z digest=sha256:f3fe972a65bd901d6ce3bbe30bc9f712ba58326643fa87c3a257b55245aa0e47

Observation 1e5ec352-5dd6-4eae-b5b9-624776d59a88 · outbound

This paper cites Vlmpc: Vision-language model predictive control for robotic manipulation,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Vlmpc: Vision-language model predictive control for robotic manipulation,

Reference 42

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source=pdf_text observed=2026-08-08T00:03:16.480335Z digest=sha256:3987ff0687c3423d6d52507fefeed80028e62672913ce6235c2cb5b1c5e942e9

Observation b5c28687-3fbd-496b-865e-d78dc4aa2b1e · outbound

This paper cites Language to Rewards for Robotic Skill Synthesis.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Language to Rewards for Robotic Skill Synthesis

Reference 43

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source=pdf_text observed=2026-08-08T00:03:16.484627Z digest=sha256:5d47383c42779f40428537f4141710dd5ee9c4cf41f4e8c26ab412c0c7027b80

Observation 62608a93-1a11-4020-9270-b67231964b8e · outbound

This paper cites Eureka: Human-Level Reward Design via Coding Large Language Models.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Eureka: Human-Level Reward Design via Coding Large Language Models

Reference 44

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source=pdf_text observed=2026-08-08T00:03:16.489420Z digest=sha256:c3b158c6585c48087b4036c11079348f4f965e2e6265a50eb0ec2a05f7e5466b

Observation c29644e2-6885-45e1-bf47-879082ef0151 · outbound

This paper cites DrEureka: Language Model Guided Sim-To-Real Transfer.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards DrEureka: Language Model Guided Sim-To-Real Transfer

Reference 45

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source=pdf_text observed=2026-08-08T00:03:16.494550Z digest=sha256:7a85e1362719848166310d89411e31fa1a13e694cd7b4344a9c2c53e598de7d3

Observation a102b346-d097-4ca6-aa9d-2dbaf6820c14 · outbound

This paper cites Text2Reward: Reward Shaping with Language Models for Reinforcement Learning.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Text2Reward: Reward Shaping with Language Models for Reinforcement Learning

Reference 46

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source=pdf_text observed=2026-08-08T00:03:16.500490Z digest=sha256:0fe17a4f02d76d697ae44f2941bde43414b879d5adebfd175512c1b51926a555

Observation 7d63cf55-2465-4972-a54b-66ad03d96750 · outbound

This paper cites Real- time perception meets reactive motion generation,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Real- time perception meets reactive motion generation,

Reference 47

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source=pdf_text observed=2026-08-08T00:03:16.505774Z digest=sha256:2f799192d4e1a7d6aa3d7b5cef8e1ffd5e6483eb105d5d8217b3b97f1bebc39c

Observation 75742f90-7033-4095-97f9-d0ba89f41c3a · outbound

This paper cites You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration

Reference 48

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source=pdf_text observed=2026-08-08T00:03:16.510856Z digest=sha256:25c0e7788aade50fdc0721f126364e91c98f8939ff27e05107c7aa84a576790a

Observation bb9f0c69-932f-457a-a79d-73effc0e24cc · outbound

This paper cites One-2-3-45++: Fast single image to 3d objects with consistent multi-view generation and 3d diffusion,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards One-2-3-45++: Fast single image to 3d objects with consistent multi-view generation and 3d diffusion,

Reference 49

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source=pdf_text observed=2026-08-08T00:03:16.516080Z digest=sha256:95c943d5d4c3c582a19a05765a66bd469bb9dff7be97f1702093a3db8ee9a409

Observation 3d0621d7-2005-48c6-883b-fb227736d911 · outbound

This paper cites Sparp: Fast 3d object reconstruction and pose estimation from sparse views,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Sparp: Fast 3d object reconstruction and pose estimation from sparse views,

Reference 50

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source=pdf_text observed=2026-08-08T00:03:16.521047Z digest=sha256:197870fcd9cd7170294c34faacc2e3487859ac5c8625e8d33463ccdbcc61bba7

Observation 07e10d96-a663-4f26-b5af-33c8d94f09ac · outbound

This paper cites Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model

Reference 51

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source=pdf_text observed=2026-08-08T00:03:16.525937Z digest=sha256:88bd4de6a60cfaed7e4574b33a17147f20d77ecf29188132f55376541f7ce10e

Observation 1b538cba-dfac-41b6-b9ca-fd4557694eca · outbound

This paper cites Zero-1-to-3: Zero-shot one image to 3d object,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Zero-1-to-3: Zero-shot one image to 3d object,

Reference 52

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source=pdf_text observed=2026-08-08T00:03:16.531439Z digest=sha256:226f9f4c7995e949c6ecba4b80ca2d542f924e9ec81614f84bff41d11ed3f3d2

Observation e6d82dd1-e8e4-41ab-9a62-a308126c2e00 · outbound

This paper cites Get3d: A generative model of high quality 3d textured shapes learned from images,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Get3d: A generative model of high quality 3d textured shapes learned from images,

Reference 53

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source=pdf_text observed=2026-08-08T00:03:16.536582Z digest=sha256:f66ed122b08d3d3e73b2a3a12da7c8ec3f8923509ed187642a63d624d859bc25

Observation 04e37a37-102c-4b70-a3fd-4d0045dd6b5b · outbound

This paper cites A-sdf: Learning disentangled signed distance functions for articulated shape representation,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards A-sdf: Learning disentangled signed distance functions for articulated shape representation,

Reference 54

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source=pdf_text observed=2026-08-08T00:03:16.542036Z digest=sha256:8fb8fc610e73870276b0b67b669264fa795146e0c62a958d90b07480314748e7

Observation 2e9f0d80-8d8e-4350-86eb-36970cd86470 · outbound

This paper cites Ditto: Building digital twins of articulated objects from interaction,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Ditto: Building digital twins of articulated objects from interaction,

Reference 55

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source=pdf_text observed=2026-08-08T00:03:16.546629Z digest=sha256:d61e1b0bda400b25b361d4ef59a7bb1a75a8603fe6f8cceabfe6c79e27021e18

Observation 9caf3985-cbf1-4e30-9a4a-6a1388b17753 · outbound

This paper cites Structure from Action: Learning Interactions for Articulated Object 3D Structure Discovery.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Structure from Action: Learning Interactions for Articulated Object 3D Structure Discovery

Reference 56

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source=pdf_text observed=2026-08-08T00:03:16.551554Z digest=sha256:7ebfa1a005c138d0d40515536ba0c9ac1a7eb57078dbb285ae6c32c1bec61a8d

Observation a4010356-25d8-479e-9c86-8c4a65b6fa4d · outbound

This paper cites URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images

Reference 57

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source=pdf_text observed=2026-08-08T00:03:16.556855Z digest=sha256:f0d8be6c5ec1e21891f03304f49cc69bdb782f0a3fabdb10851da2545b52af31

Observation 3d333903-7b7c-4472-bdc8-e844087814d8 · outbound

This paper cites Real2Code: Reconstruct Articulated Objects via Code Generation.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Real2Code: Reconstruct Articulated Objects via Code Generation

Reference 58

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source=pdf_text observed=2026-08-08T00:03:16.561525Z digest=sha256:8abb9ab3e3dccfe0d98d697b113d8073baa2be9a883dcb86fef1135186f11a83

Observation af77e4de-66e1-4859-884d-d40d7ef01dea · outbound

This paper cites Paris: Part-level recon- struction and motion analysis for articulated objects,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Paris: Part-level recon- struction and motion analysis for articulated objects,

Reference 59

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source=pdf_text observed=2026-08-08T00:03:16.566123Z digest=sha256:7daaf5aaae8cf328545447d74cc2429307c15ffea8341864ab1ba1b6cae9364d

Observation 4e786dbc-32f1-41a2-b17a-6c567ed5a538 · outbound

This paper cites Cage: Con- trollable articulation generation,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Cage: Con- trollable articulation generation,

Reference 60

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source=pdf_text observed=2026-08-08T00:03:16.570709Z digest=sha256:792086ef844b4776b50e6c9690ccc0e4a5284d3079e09fb60dccc3af42fa9f9f

Observation ca7c229c-7f2f-4a2c-98fd-5453666e2ab8 · outbound

This paper cites SINGAPO: Single Image Controlled Generation of Articulated Parts in Objects.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards SINGAPO: Single Image Controlled Generation of Articulated Parts in Objects

Reference 61

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source=pdf_text observed=2026-08-08T00:03:16.575359Z digest=sha256:98954607ae13be656f031b1ea746161185ce9b59bfe3d73feadb69de160d9d4d

Observation 5b03311d-30e7-43f3-9407-336d5d316d1b · outbound

This paper cites Occlusion-aware recon- struction and manipulation of 3d articulated objects,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Occlusion-aware recon- struction and manipulation of 3d articulated objects,

Reference 62

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source=pdf_text observed=2026-08-08T00:03:16.580461Z digest=sha256:0637da2a72fb078de534e0067cd500f9bff770765dad761518433922d55851b8

Observation a1d0c1b3-e377-423b-b87f-bc088945bc0b · outbound

This paper cites Bundlesdf: Neural 6-dof tracking and 3d reconstruction of unknown objects,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Bundlesdf: Neural 6-dof tracking and 3d reconstruction of unknown objects,

Reference 63

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source=pdf_text observed=2026-08-08T00:03:16.585255Z digest=sha256:2487557a3a2c74b47c217db2da96898c5450afb73294b7c395ed82f55439f141

Observation 4df0e853-1037-410a-815f-0e420d0edc9b · outbound

This paper cites CLIPort: What and Where Pathways for Robotic Manipulation.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards CLIPort: What and Where Pathways for Robotic Manipulation

Reference 64

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source=pdf_text observed=2026-08-08T00:03:16.590139Z digest=sha256:2df48c2baeb9da7d2e018265a508add2e093334fcec0e7af3d204ac3e0c8ef6f

Observation 0fd02d25-9392-45e1-8798-4480d4e5219f · outbound

This paper cites Transic: Sim-to-real policy transfer by learning from online correction,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Transic: Sim-to-real policy transfer by learning from online correction,

Reference 65

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source=pdf_text observed=2026-08-08T00:03:16.595186Z digest=sha256:e6ac79e5a9a86e0354327e25b39ce3d6e44f3ba7aa6e7204dbc92126ac43632f

Observation b0bff8fe-78e9-4604-9ac7-f9efefd56a88 · outbound

This paper cites Multi-skill Mobile Manipulation for Object Rearrangement.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Multi-skill Mobile Manipulation for Object Rearrangement

Reference 66

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source=pdf_text observed=2026-08-08T00:03:16.605432Z digest=sha256:c0f1f9a69f548704e216bc7bc252ec592c59bd7bcfbedd284d6e4cf05c2b6fcc

Observation a5f2b335-7871-45e3-8dd5-056af89c77c5 · outbound

This paper cites HomeRobot: Open-Vocabulary Mobile Manipulation.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards HomeRobot: Open-Vocabulary Mobile Manipulation

Reference 67

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source=pdf_text observed=2026-08-08T00:03:16.610183Z digest=sha256:d93bfa7a7d645d9192e23d39fde24574d338b94fd4a27e5195934e27a1eb3fad

Observation b3806a66-12bf-4dfb-b5ca-eebb8f5602b6 · outbound

This paper cites Dynamic Handover: Throw and Catch with Bimanual Hands.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Dynamic Handover: Throw and Catch with Bimanual Hands

Reference 68

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source=pdf_text observed=2026-08-08T00:03:16.615179Z digest=sha256:454c79053967ad20264cc6a2be70cf4071ac2bf3efe33768de06e0cad8fe6e2f

Observation 0410bcb5-b1dd-429a-82ee-633ace0a45f0 · outbound

This paper cites Sequential Dexterity: Chaining Dexterous Policies for Long-Horizon Manipulation.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Sequential Dexterity: Chaining Dexterous Policies for Long-Horizon Manipulation

Reference 69

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source=pdf_text observed=2026-08-08T00:03:16.620521Z digest=sha256:5fb9b51a08aaa48d98832cbb9095b130fe8b23d87cdbadf257b3a38be8be367f

Observation 470fc6e2-cae2-4a70-9afc-2fbe1116d420 · outbound

This paper cites DexPoint: Generalizable Point Cloud Reinforcement Learning for Sim-to-Real Dexterous Manipulation.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards DexPoint: Generalizable Point Cloud Reinforcement Learning for Sim-to-Real Dexterous Manipulation

Reference 70

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source=pdf_text observed=2026-08-08T00:03:16.625626Z digest=sha256:830dc8c34bbe035a9361d82a6067ae181cc212ad26927920a248675f6b7e04dc

Observation 41f75bc4-2731-4128-aff6-73f73c6e75d6 · outbound

This paper cites In-hand object rotation via rapid motor adaptation,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards In-hand object rotation via rapid motor adaptation,

Reference 71

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.630924Z digest=sha256:c89739bac507267bb403a000af4f2ed0c31f9a4debca28fa38107cef2b0ab82b

Observation c51f514b-42a6-4fa3-b125-8258f75defa5 · outbound

This paper cites Rotating without Seeing: Towards In-hand Dexterity through Touch.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Rotating without Seeing: Towards In-hand Dexterity through Touch

Reference 72

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.635725Z digest=sha256:c9a91b95da3d9cfabd4c776859a8c581014613e42598072ed4fc77d97cd4e6da

Observation 2267b1a2-56e4-446a-9802-32275240a9e6 · outbound

This paper cites RMA: rapid motor adaptation for legged robots,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards RMA: rapid motor adaptation for legged robots,

Reference 73

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.640594Z digest=sha256:12a600f4b095b06afff61ad2c8efb7758eab07acf25b9c44b26f401c8492af7a

Observation 8af8501f-9335-4193-939f-17cf7b24bf87 · outbound

This paper cites Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion

Reference 74

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.645397Z digest=sha256:e398a8ccc5107ccde819f7e4f94c4cb37c3481679b978a90d125b3d3cb5a3ec3

Observation 44239ca9-7d85-4244-aada-2d6212c54b4e · outbound

This paper cites Sim-to-Real: Learning Agile Locomotion For Quadruped Robots.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Sim-to-Real: Learning Agile Locomotion For Quadruped Robots

Reference 75

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.650419Z digest=sha256:e963439be6e00fd6a6cc195149aa2023c46c18f0b4dddbec500030f13a2fa8ae

Observation 3e08b070-9a30-4f22-ada5-63d07d0d8c4b · outbound

This paper cites Sim2Real2Sim: Bridging the Gap Between Simulation and Real-World in Flexible Object Manipulation.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Sim2Real2Sim: Bridging the Gap Between Simulation and Real-World in Flexible Object Manipulation

Reference 76

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.655603Z digest=sha256:94fcb5ac118d6ae64ba522150f67d9440494c6fb7dcb659a9c2f1af80b724d2d

Observation c63dd2d0-66f6-49f5-b0db-96a9bfaaa7d5 · outbound

This paper cites Planar Robot Casting with Real2Sim2Real Self-Supervised Learning.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Planar Robot Casting with Real2Sim2Real Self-Supervised Learning

Reference 77

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.661092Z digest=sha256:67287b6502d403ab722797b759c3b2b591e232056c35b1d032b6dd2bd93c9fb9

Observation 6a6e2641-724a-494a-a6d3-e5e4f7539323 · outbound

This paper cites Using simulation and domain adaptation to improve efficiency of deep robotic grasping,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Using simulation and domain adaptation to improve efficiency of deep robotic grasping,

Reference 78

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.666271Z digest=sha256:f2cfc9d9054019efda6eb246167dbe0d159d06b8befa9dd5dd7fb9165c235493

Observation 9b86c0da-750c-4ebe-b4d5-90e5f209480c · outbound

This paper cites Meta Reinforcement Learning for Sim-to-real Domain Adaptation.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Meta Reinforcement Learning for Sim-to-real Domain Adaptation

Reference 79

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verified exact
local_arxiv, observed 2026-08-08T00:03:17.033527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.671206Z digest=sha256:7cd8769548353c354fd49f7a07c8024464f69b34799f739823f714005c9fd2a2

Observation df8ff7a0-8582-47d5-880c-0db70b1480a6 · outbound

This paper cites Rl-cyclegan: Reinforcement learning aware simulation-to-real,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Rl-cyclegan: Reinforcement learning aware simulation-to-real,

Reference 80

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verified fuzzy
raw_fallback, observed 2026-08-08T00:03:33.543582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.676293Z digest=sha256:a2413900a4828737036bbe0fa77e1263ea6f27a6c405b8bab291ce44d3e74798

Observation 655ca09d-0f59-4ea9-b68e-a20f6599dff3 · outbound

This paper cites Sim-to-real via sim-to-sim: Data-efficient robotic grasping via randomized-to- canonical adaptation networks,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Sim-to-real via sim-to-sim: Data-efficient robotic grasping via randomized-to- canonical adaptation networks,

Reference 81

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verified fuzzy
raw_fallback, observed 2026-08-08T00:03:33.527122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.691287Z digest=sha256:e828953cacfc39f538fbdb9ca28bfbd2f068f5cc7407e83d5d98814885d0f6d3

Observation 918868db-59eb-4783-8598-70603d5f4824 · outbound

This paper cites Bayesian imi- tation learning for end-to-end mobile manipulation,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Bayesian imi- tation learning for end-to-end mobile manipulation,

Reference 82

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verified fuzzy
raw_fallback, observed 2026-08-08T00:03:33.510694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.695854Z digest=sha256:3e39549d0aaf7466b06d17a736c8831c87cae75fe0aeb736d7056c57d16dfc20

Observation b5666bd5-45f2-45b0-b831-78a7b5ec4c90 · outbound

This paper cites Solving Rubik's Cube with a Robot Hand.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Solving Rubik's Cube with a Robot Hand

Reference 83

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.700270Z digest=sha256:7ff4b0060e8ae9f0753bb3999e1fa29c24d86a79d03bfa90fe2126fe9bf065bd

Observation 5f4da67b-ac22-4494-bd3d-7abc12bf1fdb · outbound

This paper cites Domain randomization for transferring deep neural networks from simulation to the real world,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Domain randomization for transferring deep neural networks from simulation to the real world,

Reference 84

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verified fuzzy
raw_fallback, observed 2026-08-08T00:03:33.495677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.705325Z digest=sha256:f1e51d852b8d00869b14ad1f53ce4784e4eb003f1f51fd0f64efe083a9a1098c

Observation 939e7cb9-bde7-4797-8727-41a56f1648e5 · outbound

This paper cites BayesSimIG: Scalable Parameter Inference for Adaptive Domain Randomization with IsaacGym.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards BayesSimIG: Scalable Parameter Inference for Adaptive Domain Randomization with IsaacGym

Reference 85

Resolution
verified exact
local_arxiv, observed 2026-08-08T00:03:16.973687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.709726Z digest=sha256:4ccf8055e878ff51f1fca8ca324fbb6e5a9dc49bfd56d72345bf41dc6e68a9fd

Observation fc9229a3-c9f4-4ddd-a822-f74f97c35a72 · outbound

This paper cites Learning quadrupedal locomotion over challenging terrain,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Learning quadrupedal locomotion over challenging terrain,

Reference 86

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.714378Z digest=sha256:01d72d4dcae7d2284c30a84531f3086a003bd543863e12bfcefef52121cb86a5

Observation 83685c33-80c8-43bc-8796-64bb8bf8a06f · outbound

This paper cites Sim-to- real transfer of robotic control with dynamics randomization,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Sim-to- real transfer of robotic control with dynamics randomization,

Reference 87

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verified fuzzy
raw_fallback, observed 2026-08-08T00:03:33.454347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.718797Z digest=sha256:a2a08da4cde303f773dfc4b6c18b5cac3f12402ff3d42d386de1342ea13fbbb1

Observation c7875af2-470e-413c-bf9d-ae829df6fec6 · outbound

This paper cites Closing the sim-to-real loop: Adapting simulation randomization with real world experience,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Closing the sim-to-real loop: Adapting simulation randomization with real world experience,

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:03:33.364032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.723039Z digest=sha256:c6d46c1dbe2e12eb53eb7f5de95673843a5ef2dfe7d43d876ebf805bcebf6a03

Observation 96cb6d3b-45f7-4b44-9cc0-5449c84b15c6 · outbound

This paper cites Reconciling Reality through Simulation: A Real-to-Sim-to-Real Approach for Robust Manipulation.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Reconciling Reality through Simulation: A Real-to-Sim-to-Real Approach for Robust Manipulation

Reference 89

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.727408Z digest=sha256:d26f79bc1bba28b9b21e8a2df9700be082efc30ea37eabff9249b78903ced5d9

Observation 2511b640-3fc8-4757-8395-1306a854eb46 · outbound

This paper cites FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects

Reference 90

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.732128Z digest=sha256:2bbfa9e97cb702eef8cc25dbfedfc083cbbb1a4fee6431cfa9c03086faa9ea97

Observation a0154d1e-f285-4fe7-88e9-b2abef40519c · outbound

This paper cites Isaac gym: High performance gpu-based physics simu- lation for robot learning,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Isaac gym: High performance gpu-based physics simu- lation for robot learning,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:03:33.291338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.736463Z digest=sha256:0e498a68dfd70e3dfeeedbe40153a1d6c266b14d7a0dc6960111b3cc7cafa94d

Observation 9946b09c-0387-4146-b78a-7fac5a80ad38 · outbound

This paper cites Proximal Policy Optimization Algorithms.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Proximal Policy Optimization Algorithms

Reference 92

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T00:03:16.741065Z digest=sha256:ab24681ad8ec089a66c60b8390377d5ac1481e472ffc08cc75b2c33c87e403c2

Observation db9a0076-e3d1-47fc-ac81-de6d76c7216d · outbound

This paper cites Actor-critic algorithms,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Actor-critic algorithms,

Reference 93

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source=pdf_text observed=2026-08-08T00:03:16.745497Z digest=sha256:1647598a52f960e30e74095a4fdda2978b45f0b83e2c22c72b6056058ab30eb7

Observation fb03dff6-e79c-4f1b-a6a7-497ce90976d9 · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 94

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.749999Z digest=sha256:fd1ad6d9b746775a49e37ef72f08d9909539ce90044c263cecfe57385aae4c27

Observation 48235b7d-9590-4daf-9aa1-02d1cd9200c4 · outbound

This paper cites Anygrasp: Robust and efficient grasp perception in spatial and temporal domains,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Anygrasp: Robust and efficient grasp perception in spatial and temporal domains,

Reference 95

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.755082Z digest=sha256:1e803f75ca2d8d49dfc4ec5899433d73a6c8473ee14697c5344f3c9ed33a8bf7

Observation e19f28ed-b16e-4dd8-9bbe-ad8ce9ad5440 · outbound

This paper cites Deep reinforce- ment learning for robotic manipulation with asynchronous off-policy updates,.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Deep reinforce- ment learning for robotic manipulation with asynchronous off-policy updates,

Reference 96

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verified fuzzy
raw_fallback, observed 2026-08-08T00:03:33.203701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T00:03:16.759988Z digest=sha256:5cf1afbac2993554d0983912a97de1b5629da5cac33e97cb2659ba0005563fb9

Observation 5d116be6-bf3c-4fa1-a6dd-ff8cc3b1431a · outbound

This paper cites Data-efficient Deep Reinforcement Learning for Dexterous Manipulation.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Data-efficient Deep Reinforcement Learning for Dexterous Manipulation

Reference 97

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.764736Z digest=sha256:2191f9cbf532858ddccf4a0162667a1d86bd176f0c148b802e0092648fca1323

Observation fd0364ba-02a4-4b1c-ac53-44544d5f3b75 · outbound

This paper cites Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards

Reference 98

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source=pdf_text observed=2026-08-08T00:03:16.769641Z digest=sha256:911a4191355a4c8585a23f4d59a84e8633ee02e4acb176ba485282967ba90e4c

Observation a106ce4d-ad29-4721-87e4-0e11f1c83468 · outbound

This paper cites Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations.

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations

Reference 99

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T00:03:16.774897Z digest=sha256:8ed17f74e9367b26f03e1e5e1fbe3fe9f621773aa2b2d7619a9b742c429b65f2

Observation 88bac22c-7408-4409-97af-615540a10443 · outbound

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

A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards Spatialvlm: Endowing vision-language models with spatial reasoning capabilities,

Reference 100

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source=pdf_text observed=2026-08-08T00:03:16.780089Z digest=sha256:25a4baf0c859af7292263830a488c8b027b8a02e2d9860a9cf68d430eb6d2048

Pith citing papers

Observation 680fdbc5-9dcc-42c6-94f7-1772805f9740 · inbound

AntiGrounding: Lifting Robotic Actions into VLM Representation Space for Decision Making cites this paper.

AntiGrounding: Lifting Robotic Actions into VLM Representation Space for Decision Making A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 55

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no resolver link, observed 2026-08-07T00:57:29.723051Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:57:29.723051Z digest=sha256:c0202afd631427b507e1f7ba388ad79ab9b87c9c5ca7dffba942c5ab769f33ba

Observation b1375379-f124-451c-aa10-bf2537dc0f4e · inbound

T-Rex: Task-Adaptive Spatial Representation Extraction for Robotic Manipulation with Vision-Language Models cites this paper.

T-Rex: Task-Adaptive Spatial Representation Extraction for Robotic Manipulation with Vision-Language Models A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:03.998541Z digest=sha256:7a944c67afa8e4e41e7aa16481345487c0f7af910e8e511eaaa3188fdb47b794

Observation cbb5d694-b31c-47df-841f-462af41c88b1 · inbound

Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations cites this paper.

Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 92

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arxiv_id, observed 2026-05-19T06:37:07.459812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T06:36:13.144868Z digest=sha256:7afcf30334b8d0df2d2576426c09cd738749e25c97428278b28f33b201fec06c

Observation c3bd9742-0f67-46a1-9bb5-8663222f2895 · inbound

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training cites this paper.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:53:06.245250Z digest=sha256:8fe9ea619331ef74f0b3fc76f611c6bec6604ea85fb19bf7c3a9845310f11b18

Observation e48e9bbf-228b-45ee-9df6-127ffd6cfe68 · inbound

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth cites this paper.

"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 64

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no resolver link, observed 2026-08-06T05:15:42.737737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:15:42.737737Z digest=sha256:4a9e1ddd5c0abd0719ff4fea50757dbbe132db2c98a0f90d2894283611d17ba4

Observation 16a0106c-88aa-4b60-a40b-59df9e41021c · inbound

VLM4D: Towards Spatiotemporal Awareness in Vision Language Models cites this paper.

VLM4D: Towards Spatiotemporal Awareness in Vision Language Models A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-06T05:12:37.457514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:12:37.457514Z digest=sha256:5772c1d07564487374ec6e5ee32298f7126c308705cf63cf261826214593744e

Observation 05f18a08-58d8-41cb-a3d9-e8e08043ca47 · inbound

IGen: Scalable Data Generation for Robot Learning from Open-World Images cites this paper.

IGen: Scalable Data Generation for Robot Learning from Open-World Images A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-17T02:58:54.973570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T02:58:36.214948Z digest=sha256:f536e6fa4aa0e1e6e9fb8c5cfcf24b37c66433288a41037377540abc981b95fd

Observation b803f424-e42c-467b-9638-48bffd3de407 · inbound

PLanAR: Planning-Language-Grounded Agentic Reasoning for Robot Manipulation cites this paper.

PLanAR: Planning-Language-Grounded Agentic Reasoning for Robot Manipulation A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-03T05:38:49.656397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:38:49.656397Z digest=sha256:d7df9fca72379c5f278980106d8e1b31a41ebe68197ca76579b2fe6398930782

Observation 688f2f83-d14a-4173-8092-2f5a8882a798 · inbound

Pix2Act: Image-Space Manipulation Policies with Equivariant Augmentation cites this paper.

Pix2Act: Image-Space Manipulation Policies with Equivariant Augmentation A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 46

Resolution
unresolved
no resolver link, observed 2026-07-14T06:33:12.974578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T06:33:12.974578Z digest=sha256:0cbd57930988390cac0fb53739350b1387c4937a66fc25928ce0929c9cb9b78a

Observation fabdcdc1-322a-45ad-9cbf-33661fd7b2f2 · inbound

LEACL: LLM-Enhanced Automatic Curriculum Learning for Reinforcement Learning in Long-Horizon Manipulation Tasks cites this paper.

LEACL: LLM-Enhanced Automatic Curriculum Learning for Reinforcement Learning in Long-Horizon Manipulation Tasks A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 23

Resolution
unresolved
no resolver link, observed 2026-07-30T20:27:56.604936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T20:27:56.604936Z digest=sha256:dbc93e9e25084feb8926f32f77b1a54e46380b252d5249c87af9485aba842680