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Paper Citation Record · LEDGER

Toward Sim-to-Real Directional Semantic Grasping

As of 19 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:1909.02075.

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

pith.paper-citation-record.v1
1909.02075 v3

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:04:27.499083Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

  • verified exact2
  • verified fuzzy34
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d8b441f5-749f-493d-9513-43d5a121e3c5 · outbound

This paper cites Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a multi-armed bandit model with correlated rewards,.

Toward Sim-to-Real Directional Semantic Grasping Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a multi-armed bandit model with correlated rewards,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.173819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 1ab6266b-a890-4cdd-9404-8571a65fdd3b · outbound

This paper cites Dex-Net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics,.

Toward Sim-to-Real Directional Semantic Grasping Dex-Net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics,

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-14T05:04:27.319103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:04:27.319103Z digest=sha256:1b946cc56f5e04602c06d59a429e7a21cf7eff1f4f6ed8ecf0f3e0b23b15a415

Observation 0345d0c5-5dc3-4c27-a347-07e31f7d5d79 · outbound

This paper cites Learning deep policies for robot bin picking by simulating robust grasping sequences,.

Toward Sim-to-Real Directional Semantic Grasping Learning deep policies for robot bin picking by simulating robust grasping sequences,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.151919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 115c2a23-cca3-44fd-b872-89430d1d7a19 · outbound

This paper cites Dex- Net 3.0: Computing robust robot suction grasp targets in point clouds using a new analytic model and deep learning,.

Toward Sim-to-Real Directional Semantic Grasping Dex- Net 3.0: Computing robust robot suction grasp targets in point clouds using a new analytic model and deep learning,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.140011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.328353Z digest=sha256:76135fccdb81f5dcc59ff890179b43f0292b4fed42d0477f07b1b746f5941a2f

Observation 41866d4f-2dde-46ec-84b8-8108d2abddec · outbound

This paper cites End- to-end learning of semantic grasping,.

Toward Sim-to-Real Directional Semantic Grasping End- to-end learning of semantic grasping,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.126703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.333259Z digest=sha256:c4e60378195938b80f22235485e1845c35c0cad0a9a3156a730a4d499fe59278

Observation 22e027f8-6c3d-4b89-ad3e-74a8ff352d3c · outbound

This paper cites Human-level control through deep reinforcement learning,.

Toward Sim-to-Real Directional Semantic Grasping Human-level control through deep reinforcement learning,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.114662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.338309Z digest=sha256:c0551289a43a3c875c0194d87baee2623217a140e495f95132cea6bcddab37a3

Observation 0f4c9594-4ab8-49f3-8960-5649640df5d1 · outbound

This paper cites Continuous control with deep reinforce- ment learning,.

Toward Sim-to-Real Directional Semantic Grasping Continuous control with deep reinforce- ment learning,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.101917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.343087Z digest=sha256:d5afeaeb1e5cd0c3d5536135aacdd8d42a0bc8a20a1e11b857d3b8607f1c2443

Observation 75f86fb0-ffab-45fd-aa99-2b2901fbc005 · outbound

This paper cites Deep reinforcement learning with double Q-learning,.

Toward Sim-to-Real Directional Semantic Grasping Deep reinforcement learning with double Q-learning,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.087307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.348491Z digest=sha256:e66740bf99523a3f236154f29f36606aa1a3a450f74cbc379665615cedebbd3e

Observation ba7474be-4a73-4d74-aaa8-3660d0e8a1e7 · outbound

This paper cites Dropout: A simple way to prevent neural networks from overfitting,.

Toward Sim-to-Real Directional Semantic Grasping Dropout: A simple way to prevent neural networks from overfitting,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.072434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.352486Z digest=sha256:ce5e6638641e0a0a73d4453a748cedecd9a733a8487de8e03dcac52efa0943d6

Observation 7167d678-922d-4260-90ee-722768d01780 · outbound

This paper cites Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection,.

Toward Sim-to-Real Directional Semantic Grasping Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.057693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.356280Z digest=sha256:bd1f127a91c198cd310b387025f0d122f35b6403c29abb954bc81c574ad76df0

Observation 3aba4582-7ac7-4c82-9c52-4463887d6828 · outbound

This paper cites Deep reinforcement learning for vision-based robotic grasping: A simulated comparative evaluation of off-policy methods,.

Toward Sim-to-Real Directional Semantic Grasping Deep reinforcement learning for vision-based robotic grasping: A simulated comparative evaluation of off-policy methods,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.042988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.360151Z digest=sha256:bd1195c185ce10793e9b790a6d78afbea8126879b9c463fb301b7b8aeb180f72

Observation 0c0eaf41-faf5-4534-ad97-04375110b61c · outbound

This paper cites A tutorial on the cross-entropy method,.

Toward Sim-to-Real Directional Semantic Grasping A tutorial on the cross-entropy method,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.029376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.364273Z digest=sha256:b411c5c3c405cf39551a705b3df5ee0db51df81fc70dae137ba8f04bfab1dff7

Observation 011e2176-4c5c-4c72-911d-bfb4f2bc21f3 · outbound

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

Toward Sim-to-Real Directional Semantic Grasping Domain randomization for transferring deep neural networks from simulation to the real world,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T05:04:27.368175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:04:27.368175Z digest=sha256:3e57375a609e9e914c761e4fdf28310a4227df1607e2ed23a91b07577eb9679a

Observation e659e094-c36f-4deb-ad6c-ce1f4eb44e6f · outbound

This paper cites Deep object pose estimation for semantic robotic grasping of household objects,.

Toward Sim-to-Real Directional Semantic Grasping Deep object pose estimation for semantic robotic grasping of household objects,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:28.007415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.372178Z digest=sha256:e651196be41e455c4b713d74b258d74139c4d32d33058feb9452434da960d890

Observation 09819cb9-6ecb-48c5-bcda-cde4638df818 · outbound

This paper cites MuJoCo: A physics engine for model-based control,.

Toward Sim-to-Real Directional Semantic Grasping MuJoCo: A physics engine for model-based control,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.993706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.376674Z digest=sha256:39725359948c3fee7fdd9039cd847f947f8bbab773ae6a0650982d9bded74bda

Observation eea35e8b-4c0f-4617-bd0d-99835584792a · outbound

This paper cites V-REP: A versatile and scalable robot simulation framework,.

Toward Sim-to-Real Directional Semantic Grasping V-REP: A versatile and scalable robot simulation framework,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.977794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.380380Z digest=sha256:29ae6d2e3e668c911bf512256cdaa75a209e9b2734af846c596bd99cc92a112d

Observation 0250fd84-80ba-4f6c-8ce2-5997deae0b51 · outbound

This paper cites PyBullet: A Python module for physics simulation in robotics, games and machine learning,.

Toward Sim-to-Real Directional Semantic Grasping PyBullet: A Python module for physics simulation in robotics, games and machine learning,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.962153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.384412Z digest=sha256:def119933693a558bb656409d624421e1da0c4f862757fd6113fc7b235d575e7

Observation e4fd5d3f-ca11-45a5-a7c6-55edb83d28b6 · outbound

This paper cites Unity: A General Platform for Intelligent Agents.

Toward Sim-to-Real Directional Semantic Grasping Unity: A General Platform for Intelligent Agents

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-14T05:04:27.387793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:04:27.387793Z digest=sha256:a932cfc2d5379e4c49705aa6b126f26b3eb5dc67be3a7d6aee67388b46e04071

Observation 7df05614-0b89-4b1a-9c0f-aae774cfd280 · outbound

This paper cites Simulation tools for model-based robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX,.

Toward Sim-to-Real Directional Semantic Grasping Simulation tools for model-based robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.948269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.392355Z digest=sha256:a86bbc8937b90853edf7edea6a4c96919a545e8d97ea3362a6fd333d9c89e3c9

Observation a9e3073f-cad0-42a7-85c2-4d386f3f1817 · outbound

This paper cites The YCB object and model set: Towards common benchmarks for manipulation research,.

Toward Sim-to-Real Directional Semantic Grasping The YCB object and model set: Towards common benchmarks for manipulation research,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.934322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.395530Z digest=sha256:d030cba19150ddbbbc066682eb8821eebef094faf87fbef55cf10087fecb2fa7

Observation 2dc2009b-faa3-4616-bae4-39db0f4d360f · outbound

This paper cites Benchmarking in manipulation research: Using the Yale-CMU- Berkeley object and model set,.

Toward Sim-to-Real Directional Semantic Grasping Benchmarking in manipulation research: Using the Yale-CMU- Berkeley object and model set,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.916998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.398910Z digest=sha256:627593f038d417201cb926b4f923f0368f43c3a02a05de5945c395dbe4726e77

Observation 02036b62-f72b-4229-9f27-929fefdd5934 · outbound

This paper cites Closing the loop for robotic grasping: A real-time, generative grasp synthesis approach,.

Toward Sim-to-Real Directional Semantic Grasping Closing the loop for robotic grasping: A real-time, generative grasp synthesis approach,

Reference 22

Resolution
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no resolver link, observed 2026-08-14T05:04:27.402505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:04:27.402505Z digest=sha256:9e950cf60d92ee47812d346cad9a4fe61a807c8d75c53d07c48288cfc247bce5

Observation a47ee608-d06b-4478-8d44-4de97a1352df · outbound

This paper cites Cartman: The low-cost Cartesian manipulator that won the Amazon Robotics Challenge,.

Toward Sim-to-Real Directional Semantic Grasping Cartman: The low-cost Cartesian manipulator that won the Amazon Robotics Challenge,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.893066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.405919Z digest=sha256:471455c41911e23142ae02bc969eb7ede681df19999168fa7667adb5505a7633

Observation d2395efb-c3d1-4a06-b76b-32be10ce72eb · outbound

This paper cites Multi-Task Domain Adaptation for Deep Learning of Instance Grasping from Simulation.

Toward Sim-to-Real Directional Semantic Grasping Multi-Task Domain Adaptation for Deep Learning of Instance Grasping from Simulation

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-14T05:04:27.629156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.409996Z digest=sha256:710029514ebd7620dbb2dfe28f281a8f0c918c3c23bcfdad52797794dc310975

Observation d2743101-76f6-4a9f-8054-77dd97751eaa · outbound

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

Toward Sim-to-Real Directional Semantic Grasping Using simulation and domain adaptation to improve efficiency of deep robotic grasping,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.880701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.414082Z digest=sha256:8febc64ed5d18e78aaa9c1b6eaedbc34e69c06ea35b0a0b5f0d2062c8909a4d2

Observation 272df56b-e03b-4920-8b93-4923b7a69d59 · outbound

This paper cites Adversarial Discriminative Sim-to-real Transfer of Visuo-motor Policies.

Toward Sim-to-Real Directional Semantic Grasping Adversarial Discriminative Sim-to-real Transfer of Visuo-motor Policies

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-08-14T05:04:27.607218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.418150Z digest=sha256:71216b660fd77e398e074950140754db9ebfdcaecfc4df76ecf7ba987f8fedbb

Observation d56d332b-9e3e-4e19-bee7-c514925c6252 · outbound

This paper cites Sim2Real viewpoint invariant visual servoing by recurrent control,.

Toward Sim-to-Real Directional Semantic Grasping Sim2Real viewpoint invariant visual servoing by recurrent control,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.867579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.422528Z digest=sha256:d93c0e011a0b009a98c3b15c15f2c18dca36c7fa15cf7ddcf08476270fe7e0ea

Observation 91ac2ad4-897d-45bf-ad22-a73b4d112301 · outbound

This paper cites Transferring end-to-end visuomotor control from simulation to real world for a multi-stage task,.

Toward Sim-to-Real Directional Semantic Grasping Transferring end-to-end visuomotor control from simulation to real world for a multi-stage task,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.852196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.426370Z digest=sha256:2921f544ab12cb301aa143ee6358d40a163491808cba58dc2016a4cfc54c478d

Observation f21ddd97-616a-4e89-a884-e6e1f03f6f0a · outbound

This paper cites Sim-to-Real Reinforcement Learning for Deformable Object Manipulation.

Toward Sim-to-Real Directional Semantic Grasping Sim-to-Real Reinforcement Learning for Deformable Object Manipulation

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-14T05:04:27.430206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:04:27.430206Z digest=sha256:dad701ad004320019eab6f161baf7d0c1f1389d49d984ed6de614ad654108f2b

Observation 232b6e71-5cd1-4592-8366-601241bcbb41 · outbound

This paper cites Sim-to-real transfer of accurate grasping with eye-in-hand observations and continuous control,.

Toward Sim-to-Real Directional Semantic Grasping Sim-to-real transfer of accurate grasping with eye-in-hand observations and continuous control,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.828920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.434856Z digest=sha256:70405fe6c85650669d931c1202d7f2735aea7b8f67c02cbc1fee7630c9ac086b

Observation a35d84fc-bd2a-4095-8c41-d82b1a4ad3f2 · outbound

This paper cites Learning a visuo- motor controller for real world robotic grasping using simulated depth images,.

Toward Sim-to-Real Directional Semantic Grasping Learning a visuo- motor controller for real world robotic grasping using simulated depth images,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.814325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.438741Z digest=sha256:a2019c07b2ab7fab23739212ef306efc2493372ef1cd057472a5de1acf9a43a4

Observation ced256fb-a775-4d9b-a65d-dce23b5f1b37 · outbound

This paper cites Experiments with hierarchical reinforcement learning of multiple grasping policies,.

Toward Sim-to-Real Directional Semantic Grasping Experiments with hierarchical reinforcement learning of multiple grasping policies,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.800515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.444662Z digest=sha256:c2599a67825abaad51275c985167abb09c7eb76fdbaee6bb8713a86b4dd4ccf7

Observation ea65ed59-f713-4da4-bc6d-0961e7a29c6d · outbound

This paper cites Learning task-oriented grasping for tool manipulation from simulated self-supervision,.

Toward Sim-to-Real Directional Semantic Grasping Learning task-oriented grasping for tool manipulation from simulated self-supervision,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.786267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.449126Z digest=sha256:dff579129a50f2ad082f9050fe36b47c60c974bc4814c8bc4f7e7efbed90e30c

Observation ff564b50-83f1-4fca-a631-10161b63c6d6 · outbound

This paper cites The MOPED framework: Object recognition and pose estimation for manipulation,.

Toward Sim-to-Real Directional Semantic Grasping The MOPED framework: Object recognition and pose estimation for manipulation,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.771820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.453556Z digest=sha256:ef3de2b94d061e709f6eb11ad110a9f438beaf2d0632f228a08562b99b35fcdb

Observation 4de636c1-2ec7-41ff-87cf-e4e803752a8c · outbound

This paper cites SimTrack: A simulation-based framework for scalable real-time object pose detection and tracking,.

Toward Sim-to-Real Directional Semantic Grasping SimTrack: A simulation-based framework for scalable real-time object pose detection and tracking,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.756775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.457633Z digest=sha256:2efc24b8bfa2a051b7caff66213433e51e5b3171f381715319b4fd51e1a79a3d

Observation 8d85a34b-4a97-4196-b558-c19368e072c6 · outbound

This paper cites Goal-directed robot manipulation through axiomatic scene estimation,.

Toward Sim-to-Real Directional Semantic Grasping Goal-directed robot manipulation through axiomatic scene estimation,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.742915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.461695Z digest=sha256:9fd95966291b1e79e7c4ca1054c95ac42ca2351d42f08c70fbbf946d4b6e7f0f

Observation 78b8a928-e8d4-47ae-bedd-5eee1cc7fabf · outbound

This paper cites Semantic robot programming for goal-directed manipulation in cluttered scenes,.

Toward Sim-to-Real Directional Semantic Grasping Semantic robot programming for goal-directed manipulation in cluttered scenes,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.726949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.466166Z digest=sha256:19c5863366a8382e5cc5f0b8a9278eb153c505e52977bbc11a6836923cbc2662

Observation ddff38fe-ab4f-428c-ab48-edba3553b0d2 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Toward Sim-to-Real Directional Semantic Grasping ShapeNet: An Information-Rich 3D Model Repository

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-14T05:04:27.475389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:04:27.475389Z digest=sha256:6adfd31353a38ff273d8f0683799ea076fa32526488805b8c1a1db645de1a270

Observation 690687f5-0581-43ab-a619-2cf1b5311f6f · outbound

This paper cites Beyond PASCAL: A bench- mark for 3D object detection in the wild,.

Toward Sim-to-Real Directional Semantic Grasping Beyond PASCAL: A bench- mark for 3D object detection in the wild,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.710056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.483256Z digest=sha256:dc5d8c7f955dfd6ed7e71a98d390afd9e6fc95db1ac17d546d88d33530cd1f47

Observation 1921782e-a65b-45f0-b8c4-c4862e0ebdf3 · outbound

This paper cites Mechanical search: Multi-step retrieval of a target object occluded by clutter,.

Toward Sim-to-Real Directional Semantic Grasping Mechanical search: Multi-step retrieval of a target object occluded by clutter,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.695688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.488243Z digest=sha256:8b2db077682908672fa2eb3603a27464e0e1f67b2f722949bd7e6193f4f33040

Observation 271bbc40-9d55-4ae1-a11e-a28371300dff · outbound

This paper cites Mastering the game of go with deep neural networks and tree search,.

Toward Sim-to-Real Directional Semantic Grasping Mastering the game of go with deep neural networks and tree search,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.680436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.493779Z digest=sha256:c02298f16d7981d9c4a89f76fd37f9d3f27f7a0654f7744eefa6a1006430bc9a

Observation 7ca66614-1bec-4dd0-9399-887e643311c2 · outbound

This paper cites 3D simulation for robot arm control with deep Q-learning,.

Toward Sim-to-Real Directional Semantic Grasping 3D simulation for robot arm control with deep Q-learning,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:04:27.665567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-14T05:04:27.499083Z digest=sha256:b8586c476c3cdc664a7775355530b5c3bfc0c32fd5c5e7002f4fe6724f748893

Pith citing papers

No inbound Pith citation observations are available.