GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System | Paper Citation Record

Observation cfee9e70-49c4-4cf5-8a9d-122acf332be3 · outbound

This paper cites A survey on learning-based robotic grasping,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System A survey on learning-based robotic grasping,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:58.478787Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e7a68425-69ff-4b33-9d53-0eeba8527e39 · outbound

This paper cites Review of deep learning methods in robotic grasp detection,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Review of deep learning methods in robotic grasp detection,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:58.301325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 33f42aac-41b3-4cef-8846-55df79a7399f · outbound

This paper cites Real-time grasp detection using convo- lutional neural networks,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Real-time grasp detection using convo- lutional neural networks,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:58.216234Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a351e099-f783-46e0-be85-0bb5ffcedc0b · outbound

This paper cites Preparatory object reorientation for task-oriented grasping,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Preparatory object reorientation for task-oriented grasping,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:57.990560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d5401055-9c73-407c-9713-d23281855aa3 · outbound

This paper cites Jacquard: A large scale dataset for robotic grasp detection,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Jacquard: A large scale dataset for robotic grasp detection,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:57.736623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 758ec55c-540e-481f-af07-e340f97a72a0 · outbound

This paper cites Graspnet-1billion: A large- scale benchmark for general object grasping,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Graspnet-1billion: A large- scale benchmark for general object grasping,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:57.514834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2c8a2e67-60ef-4fed-b429-42222feadcc5 · outbound

This paper cites When transformer meets robotic grasping: Exploits context for efficient grasp detection,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System When transformer meets robotic grasping: Exploits context for efficient grasp detection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:57.326379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9ecc8bbb-b95d-4bf1-8501-a4206a9e5c67 · outbound

This paper cites Language-driven grasp detection,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Language-driven grasp detection,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:57.049981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 673999b0-da49-4f87-b56f-e4f97dc41a30 · outbound

This paper cites Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:20:45.178010Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation af492a5c-f929-475a-91a5-026a5773ef3d · outbound

This paper cites Language models are few-shot learners,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Language models are few-shot learners,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:56.845999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 58cb3bed-a02d-4fae-b018-f2fc2c7406a3 · outbound

This paper cites Gpt-4 technical report,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Gpt-4 technical report,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:38.778580Z

Source-reported events for the cited work

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Observation a6f4ae32-61e4-4be4-be6d-7806892cf27f · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:38.843155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 432299de-d598-41c0-a191-6184e0cb596e · outbound

This paper cites DeepSeek-V3 Technical Report.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System DeepSeek-V3 Technical Report

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:38.927491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff4ec0e8-b75c-4d34-bb41-065499fcb4fe · outbound

This paper cites Do as i can, not as i say: Grounding language in robotic affordances,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Do as i can, not as i say: Grounding language in robotic affordances,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:56.519220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a80f6429-bad9-4015-bf96-dc37fb953111 · outbound

This paper cites Progprompt: Generating situated robot task plans using large language models,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Progprompt: Generating situated robot task plans using large language models,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:56.214734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 204cacfc-e23c-453c-86b9-88e9190dcc2b · outbound

This paper cites Code as policies: Language model programs for embodied control,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Code as policies: Language model programs for embodied control,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:55.944894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1dd424ce-a6d8-46ed-8272-3fe0e0ef052c · outbound

This paper cites Socratic models: Composing zero-shot multimodal reasoning with language,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Socratic models: Composing zero-shot multimodal reasoning with language,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:55.769643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 77296287-c655-4e8f-ae5f-b6580c84e3a8 · outbound

This paper cites L3mvn: Leveraging large language models for visual target navigation,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System L3mvn: Leveraging large language models for visual target navigation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:55.431673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6cbfbcb9-892a-4ab2-b578-ab491770c62f · outbound

This paper cites Adapt: Vision-language navigation with modality-aligned action prompts,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Adapt: Vision-language navigation with modality-aligned action prompts,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:55.204823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 714b6050-5789-4027-817d-89664a20e4e5 · outbound

This paper cites Language-driven grasp detection with mask-guided attention,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Language-driven grasp detection with mask-guided attention,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:54.933331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e3b1d6ff-87d8-4504-9ed0-8eaf8ebc45c9 · outbound

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

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Cliport: What and where pathways for robotic manipulation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:54.709204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 03fa2c75-1729-4faa-96db-15822b2ac81d · outbound

This paper cites A joint modeling of vision-language-action for target- oriented grasping in clutter,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System A joint modeling of vision-language-action for target- oriented grasping in clutter,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:54.485488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1decbaf5-0f8c-4051-a14b-937639a323c3 · outbound

This paper cites Language-driven 6-dof grasp detection using negative prompt guidance,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Language-driven 6-dof grasp detection using negative prompt guidance,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:54.204834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f788f13e-2cb7-4708-931e-aed5303dcc64 · outbound

This paper cites Lightweight language-driven grasp detection using con- ditional consistency model,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Lightweight language-driven grasp detection using con- ditional consistency model,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:53.862299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cfc20712-79ad-406b-a80b-fcdfd678d3a2 · outbound

This paper cites Grasp-anything: Large-scale grasp dataset from foundation models,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Grasp-anything: Large-scale grasp dataset from foundation models,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:53.614791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7e4bb0c3-4c76-4667-9d59-4b60dcdb74ac · outbound

This paper cites Graspgpt: Leveraging semantic knowledge from a large language model for task- oriented grasping,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Graspgpt: Leveraging semantic knowledge from a large language model for task- oriented grasping,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:53.226753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d9d89094-d5b9-47f3-bc44-0f4008f8205e · outbound

This paper cites Towards open-world grasping with large vision-language models,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Towards open-world grasping with large vision-language models,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:53.016195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 79774b5f-1e34-47ca-a51d-cdaba29d8d52 · outbound

This paper cites Thinkgrasp: A vision-language system for strategic part grasping in clutter,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Thinkgrasp: A vision-language system for strategic part grasping in clutter,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:52.783774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4bf2d364-8391-42e5-bfa4-535970f895ef · outbound

This paper cites Visual programming: Compositional visual reasoning without training,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Visual programming: Compositional visual reasoning without training,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:52.365710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5d04ed58-8e94-45b7-a30c-8d99870746ed · outbound

This paper cites Chameleon: Plug-and-play compositional reasoning with large language models,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Chameleon: Plug-and-play compositional reasoning with large language models,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:52.070158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 50828b12-25b9-42a1-b4db-f929672ee366 · outbound

This paper cites Vipergpt: Visual inference via python execution for reasoning,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Vipergpt: Visual inference via python execution for reasoning,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:51.794883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation df4653e7-480d-4fb7-94b6-c5730a65c855 · outbound

This paper cites Videoagent: A memory-augmented multimodal agent for video understanding,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Videoagent: A memory-augmented multimodal agent for video understanding,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:51.509889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0f6e4bc0-1ab0-45af-8e25-d4979012532a · outbound

This paper cites RoboCoder: Robotic Learning from Basic Skills to General Tasks with Large Language Models.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System RoboCoder: Robotic Learning from Basic Skills to General Tasks with Large Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:40.532400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af9149bf-fda0-49f7-820a-eec8a5527310 · outbound

This paper cites Mp5: A multi-modal open-ended embodied system in minecraft via active perception,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Mp5: A multi-modal open-ended embodied system in minecraft via active perception,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:51.339267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5192b1bb-95ce-4675-ad7c-4fda76e82aba · outbound

This paper cites Describe, explain, plan and select: Interactive planning with large language models enables open-world multi-task agents,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Describe, explain, plan and select: Interactive planning with large language models enables open-world multi-task agents,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:51.046489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3c544802-9ba9-4d5b-acee-d2a5beac2ad2 · outbound

This paper cites Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:50.814838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bf683d6a-e217-4e51-b2ad-73a46800adbd · outbound

This paper cites Fast graspability evaluation on single depth maps for bin picking with general grippers,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Fast graspability evaluation on single depth maps for bin picking with general grippers,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:50.592284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7a692630-4884-4d83-a47e-79cc37d73899 · outbound

This paper cites Grasp quality measures: review and performance,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Grasp quality measures: review and performance,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:50.348701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f10f6f12-1dac-4855-b4fc-ce025d6950d0 · outbound

This paper cites Deep learning for detecting robotic grasps,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Deep learning for detecting robotic grasps,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:50.052152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 41f17743-2761-4d2a-b6bd-eb7afbe6343b · outbound

This paper cites Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:49.796014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 42e4d2c8-ad5a-40a6-b08b-1d312e6c06de · outbound

This paper cites Antipodal robotic grasping using generative residual convolutional neural network,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Antipodal robotic grasping using generative residual convolutional neural network,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:49.634233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5b22090c-2e84-4415-8098-3123ecb33340 · outbound

This paper cites Vl-grasp: a 6- dof interactive grasp policy for language-oriented objects in cluttered indoor scenes,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Vl-grasp: a 6- dof interactive grasp policy for language-oriented objects in cluttered indoor scenes,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:49.434408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9fb1aee6-5d1c-4308-8f46-b24c36d52bc3 · outbound

This paper cites Learning 6-dof object poses to grasp category-level objects by language instructions,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Learning 6-dof object poses to grasp category-level objects by language instructions,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:49.254959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 02da47ca-eb13-4ea0-882d-ca00ca5b0753 · outbound

This paper cites A joint network for grasp detection conditioned on natural language commands,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System A joint network for grasp detection conditioned on natural language commands,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:49.077267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2cbfa97f-36f7-4c9f-9613-01c5960b4086 · outbound

This paper cites Reasoning Grasping via Multimodal Large Language Model.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Reasoning Grasping via Multimodal Large Language Model

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:41.189053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation faad749a-b314-44ba-9912-c34dc1ef1dba · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:41.227600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a147a66-267e-42bd-ae6d-5597e9b241ca · outbound

This paper cites Hydra: A hyper agent for dynamic compositional visual reasoning,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Hydra: A hyper agent for dynamic compositional visual reasoning,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:48.917107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5ce42002-57c6-40ae-804e-f4a905d26c36 · outbound

This paper cites Visual program distillation: Distilling tools and programmatic reasoning into vision-language models,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Visual program distillation: Distilling tools and programmatic reasoning into vision-language models,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:48.671109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 36b90d28-34cd-4e24-925c-1b0637d5b54c · outbound

This paper cites CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:41.428788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 339de7b0-622d-427a-8e72-e10320022808 · outbound

This paper cites Genegpt: Augmenting large language models with domain tools for improved access to biomedical information,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Genegpt: Augmenting large language models with domain tools for improved access to biomedical information,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:48.464990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a64254bb-d18d-4680-9da3-7fad1b98e933 · outbound

This paper cites Building cooperative embodied agents modularly with large language models,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Building cooperative embodied agents modularly with large language models,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:48.251824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 57a36006-0d7f-4c47-a3af-c3ae02d75e68 · outbound

This paper cites Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:48.028266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6e2f7894-c191-4776-b22b-c5d67f5ab59b · outbound

This paper cites Learning to compose visual relations,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Learning to compose visual relations,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:47.843952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4be45bda-0ff2-400d-afec-a175b6548835 · outbound

This paper cites Cplip: zero-shot learning for histopathology with comprehensive vision-language alignment,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Cplip: zero-shot learning for histopathology with comprehensive vision-language alignment,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:47.709222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 500d0d64-2cc0-4406-9d3d-324d8247f16a · outbound

This paper cites Zero-shot object detection through vision- language embedding alignment,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Zero-shot object detection through vision- language embedding alignment,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:47.543015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 309a17b8-1804-4757-9f29-28cc4dab23e6 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:41.972161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63db8bcb-1795-46c3-9d8f-d0097cc0de0d · outbound

This paper cites MALMM: Multi-Agent Large Language Models for Zero-Shot Robotics Manipulation.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System MALMM: Multi-Agent Large Language Models for Zero-Shot Robotics Manipulation

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:42.024833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5c305f3-3ad5-4756-9dbd-d285a2702797 · outbound

This paper cites Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:42.118904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bd3b039-8bc1-4c45-9a45-2e21b8c89c8e · outbound

This paper cites Shapegrasp: Zero-shot task-oriented grasping with large language models through geometric decomposition,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Shapegrasp: Zero-shot task-oriented grasping with large language models through geometric decomposition,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:47.424671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3d7a9e15-8312-4fad-bb25-65f9802dd5ce · outbound

This paper cites MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:42.368532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00689c0d-5be4-42ec-9d5c-540bb0f09755 · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Grounding dino: Marrying dino with grounded pre-training for open-set object detection,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:47.260024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7e1e31ee-03ba-40a5-b10d-62f014e4d95f · outbound

This paper cites Going denser with open-vocabulary part segmentation,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Going denser with open-vocabulary part segmentation,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:46.737106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f292db17-dd10-4101-948c-c97482a66fed · outbound

This paper cites NBMOD: Find It and Grasp It in Noisy Background.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System NBMOD: Find It and Grasp It in Noisy Background

Reference 63

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:20:44.514806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 78a074e2-e803-4052-aeec-dd9683c90acb · outbound

This paper cites Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:42.731550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85ef4368-3eac-4b9d-a2f5-46b44ec53390 · outbound

This paper cites Towards robust monocular depth estimation: Mixing datasets for zero- shot cross-dataset transfer,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Towards robust monocular depth estimation: Mixing datasets for zero- shot cross-dataset transfer,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:46.514746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dc55bcde-017d-451e-b737-630020d5c272 · outbound

This paper cites Segment anything,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Segment anything,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:46.314732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a6724e8b-00b7-410e-85ad-67293c5a751e · outbound

This paper cites Scaling open-vocabulary object detection,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Scaling open-vocabulary object detection,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:46.134672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c45167f0-e4fe-44da-95a7-270f09aec9a1 · outbound

This paper cites Language-driven grasp detection with mask-guided at- tention,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Language-driven grasp detection with mask-guided at- tention,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:46.005098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0312bd0e-7654-4a09-a987-eb6be1cc849f · outbound

This paper cites GraspMamba: A Mamba-based Language-driven Grasp Detection Framework with Hierarchical Feature Learning.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System GraspMamba: A Mamba-based Language-driven Grasp Detection Framework with Hierarchical Feature Learning

Reference 69

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:20:44.279602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 724131e9-4f71-42b9-90cd-dda6d602113b · outbound

This paper cites GraspSAM: When Segment Anything Model Meets Grasp Detection.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System GraspSAM: When Segment Anything Model Meets Grasp Detection

Reference 70

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:20:43.804832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0367be81-da20-47eb-b16a-ad330c98c9f0 · outbound

This paper cites ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:43.355361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2da0074-c305-49a7-8ee9-1b6f0fc0f39d · outbound

This paper cites Benchmarking in manipulation research: Using the yale-cmu- berkeley object and model set,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Benchmarking in manipulation research: Using the yale-cmu- berkeley object and model set,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:45.663971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e6588256-eead-46be-a03c-b47216a53b9c · outbound

This paper cites Machine learning-based framework for optimally solving the analytical inverse kinematics for redundant manipulators,.

GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System Machine learning-based framework for optimally solving the analytical inverse kinematics for redundant manipulators,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:45.405318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Reference resolution

Outbound references

Pith citing papers