Pith. sign in

Paper Citation Record · LEDGER

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials

As of 18 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2505.21916.

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

pith.paper-citation-record.v1
2505.21916 v3

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:26:30.721159Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

39 of 39 outbound references displayed

  • verified exact2
  • verified fuzzy21
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dde0c067-a19c-4bb4-a90a-fc4a2df9b1dc · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:26.933507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:26.933507Z digest=sha256:6352fe653d682f0873c9d4eab1047bf1905b38265e5894c723a7936e8039706b

Observation 9f6e0cc4-f8e1-4751-be15-928630f409cb · outbound

This paper cites Catch it! learning to catch in flight with mobile dexterous hands,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Catch it! learning to catch in flight with mobile dexterous hands,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:36.571364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:27.044744Z digest=sha256:b78a2ba9995835d78a1e8c9c32847df4c627fc98fe42768f099c0f6a883364e8

Observation 1841f679-70c0-43e7-bdd4-f68484d81443 · outbound

This paper cites Reinforcement Learning with Foundation Priors: Let the Embodied Agent Efficiently Learn on Its Own.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Reinforcement Learning with Foundation Priors: Let the Embodied Agent Efficiently Learn on Its Own

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:27.138792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:27.138792Z digest=sha256:871222b9498729a0539fc7176cc48349829ea63807ca8164de866799f176de66

Observation 1abd5754-45bb-45f9-8ccb-57100baebb7b · outbound

This paper cites Roboagent: Generalization and efficiency in robot manipulation via semantic augmentations and action chunking,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Roboagent: Generalization and efficiency in robot manipulation via semantic augmentations and action chunking,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:36.410113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:27.219525Z digest=sha256:c8af6d660d0030f5d00b8bddcaf8b63993f810bd7255dace8d96c248a1f96a66

Observation d2e3e260-18f9-4865-bca9-c236acf5b96f · outbound

This paper cites Diffusion policy: Visuomotor policy learning via ac- tion diffusion,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Diffusion policy: Visuomotor policy learning via ac- tion diffusion,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:27.288599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:27.288599Z digest=sha256:fbae9c6a068e46b63432bde459ab317783ac0b9a1c29f928071562afbcb193c7

Observation 1a818a0e-9eb9-4d24-bcb1-cc8277653bf5 · outbound

This paper cites Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:27.372085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:27.372085Z digest=sha256:f962ad46c32505c92feda9ebdbcadfbe1c59c9eb3aba8ca82f835c9785d069be

Observation 3d9c947f-18ab-4d0e-8904-b337e9c1468b · outbound

This paper cites UMI on legs: Making manipulation policies mobile with manipulation-centric whole-body controllers,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials UMI on legs: Making manipulation policies mobile with manipulation-centric whole-body controllers,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:36.146040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:27.448258Z digest=sha256:1c5dfaa6f5db4809a97297393d258851b3529203e87d95f4afbabe55f5d9d57f

Observation 9b125b66-afd3-4529-b500-dbfee911de7b · outbound

This paper cites SKIL: Semantic Keypoint Imitation Learning for Generalizable Data-efficient Manipulation.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials SKIL: Semantic Keypoint Imitation Learning for Generalizable Data-efficient Manipulation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:27.535567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:27.535567Z digest=sha256:ec4b42a71fbb9ef3b2833963e3941f3dfdeda77c50239ef3721fbe2d4ca525ba

Observation 93f944c3-9a32-465c-8dd2-7b02c676f962 · outbound

This paper cites Rt-1: Robotics transformer for real-world control at scale,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Rt-1: Robotics transformer for real-world control at scale,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:35.947994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:27.626948Z digest=sha256:9ed6024bc0b0f3ebe36766d54e61fcbccb4c508de3dff245f60ff0888dfe8948

Observation 566b6b29-ce8c-4803-8fd9-43d9c06e3977 · outbound

This paper cites Openvla: An open-source vision-language-action model,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Openvla: An open-source vision-language-action model,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:35.717526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:27.705369Z digest=sha256:5da4121ecb85d9c45b32043c4900cd1b560869805b2b17604f5551eb3049da14

Observation 9c99f3bd-bee6-41bf-8229-358bde098955 · outbound

This paper cites RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:27.782344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:27.782344Z digest=sha256:ad8213e20abb44f63594cd48412fd45f328c94535e9dd38900802102cc7ab146

Observation 3d051b29-32ce-4515-b48c-61b8d6100d8d · outbound

This paper cites Copa: General robotic manipulation through spatial constraints of parts with foundation models,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Copa: General robotic manipulation through spatial constraints of parts with foundation models,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:35.542360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:27.870762Z digest=sha256:d40ccb012de1898b484a0d897cd9e86404da3ad6a9927d1e44a7d0c357f38717

Observation 1c315c49-60a8-468f-861c-1766ead52a0b · outbound

This paper cites Onetwovla: A unified vision-language-action model with adaptive reasoning,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Onetwovla: A unified vision-language-action model with adaptive reasoning,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:27.988402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:27.988402Z digest=sha256:548de7f258b195339c78f914784d90e1de85abc64a0815bf6791d0499a9ee4d7

Observation 3b0f671b-579c-4dbe-a7d7-2a76569d55c1 · outbound

This paper cites Tactile-VLA: Unlocking Vision-Language-Action Model's Physical Knowledge for Tactile Generalization.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Tactile-VLA: Unlocking Vision-Language-Action Model's Physical Knowledge for Tactile Generalization

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:28.067832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:28.067832Z digest=sha256:1afe486a81abee1ee256583ed845338d016766b16a6d71fe6b22e18abc948ddc

Observation 54865958-4082-4bd8-b9fe-de647e0e243e · outbound

This paper cites Itera- tive residual policy: for goal-conditioned dynamic manipulation of deformable objects,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Itera- tive residual policy: for goal-conditioned dynamic manipulation of deformable objects,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:35.319684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:28.167940Z digest=sha256:327048765507f88865f08628045f7de44fb85f1a1a6edc2805b129f3a9d63214

Observation 409f3c03-2e24-4a06-b4bb-276049887685 · outbound

This paper cites Dynamic handover: Throw and catch with bimanual hands,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Dynamic handover: Throw and catch with bimanual hands,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:35.049367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:28.264807Z digest=sha256:46850563be72c10bcb22a745882b8a79b3ba3bb2ae0ba677adaf052e15155c24

Observation 0940180c-58d3-43f0-977a-7290a7d4d1ff · outbound

This paper cites Tossing- bot: Learning to throw arbitrary objects with residual physics,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Tossing- bot: Learning to throw arbitrary objects with residual physics,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:28.365732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:28.365732Z digest=sha256:b9942ef53b20673608523d8f9d42263dc0836818aaf9b66c5962be2725642cff

Observation ed05babb-c3e0-49b7-a7b3-7bd603461c4a · outbound

This paper cites A stochastic dynamic motion planning al- gorithm for object-throwing,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials A stochastic dynamic motion planning al- gorithm for object-throwing,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:34.753541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:28.466750Z digest=sha256:7f7c1a55408426906f1300306f04e1ce785dc0b8e3751c3c43141f64ad871bf4

Observation 41f110a7-93d0-4e8e-9ed7-82de4746097a · outbound

This paper cites Optimal shape and motion planning for dynamic planar manipulation,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Optimal shape and motion planning for dynamic planar manipulation,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:34.496952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:28.614868Z digest=sha256:a7e0e1c3fd26124ff1a8de8bb43c3a136ff1b56ff3d117fe135889d49a6eff53

Observation e30fe29a-1bf1-4fcf-9ecd-486fb5b5cd6e · outbound

This paper cites Learning agile robotic locomotion skills by imitating animals,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Learning agile robotic locomotion skills by imitating animals,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:34.159475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:28.756928Z digest=sha256:a696962beaa731912a15e8565ee537b29ff53459e4e4d0b6d6d802c91fb8bebe

Observation ab0143bf-26f3-4fc1-83fa-bcf95e4a42c8 · outbound

This paper cites Tool-as-interface: Learning robot policies from human tool usage through imitation learning,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Tool-as-interface: Learning robot policies from human tool usage through imitation learning,

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:28.851555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:28.851555Z digest=sha256:c6766ac3498718109a8c07e18f0259022a75eda840952331abdc48c346627323

Observation 2c6da33a-1826-4123-8f81-98d0b68c35a3 · outbound

This paper cites Conditional Variational Auto Encoder Based Dynamic Motion for Multi-task Imitation Learning.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Conditional Variational Auto Encoder Based Dynamic Motion for Multi-task Imitation Learning

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:26:31.316019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:28.970885Z digest=sha256:46296e4cc19ec47b31e8769df801483aca28cc3d02ccaff149b8d487d7d3c6c9

Observation 654d17d7-a9b9-44b9-9e33-e6b0efd39dbd · outbound

This paper cites Whole-Body Dynamic Throwing with Legged Manipulators.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Whole-Body Dynamic Throwing with Legged Manipulators

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:26:31.122942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:29.051887Z digest=sha256:2fb0965cbacadc7fde670cb91388888e9694ac3ad220b135c917c7c5d86aee8b

Observation cc0130f0-e586-4643-85ed-78d7cda9fac6 · outbound

This paper cites Mockus, V.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Mockus, V

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:33.939466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:29.136403Z digest=sha256:d812fd546c9d41ca7dbb70c3da7c949f1315f274a5f191c0d3897c683b530152

Observation 1159557e-02ba-4e8c-9fb3-29f6535b7d1e · outbound

This paper cites Gaussian processes in machine learning,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Gaussian processes in machine learning,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:33.653150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:29.223928Z digest=sha256:17d06c527081c48a5e76ff6bc706c9f9a802b401393944f1c477e9549268e4b5

Observation fe1c5f1b-6392-4471-87cd-2ab77dfa0faa · outbound

This paper cites A ball-throwing robot with visual feedback,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials A ball-throwing robot with visual feedback,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:33.421876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:29.308002Z digest=sha256:1e7a2da9f73c070081570aaf30fe8f007efa3d9a323b1052595c445717535a32

Observation c272b6ad-0489-4fa3-be30-1fb439c7e960 · outbound

This paper cites Dynamic task execution using active parameter identification with the baxter research robot,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Dynamic task execution using active parameter identification with the baxter research robot,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:33.195062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:29.455825Z digest=sha256:6d218314dd429353f5dda4336fb919e96d3fb1e0c883d9afda100582e611e55f

Observation e46e3e95-2ae3-419d-ab66-f82cc7c1f180 · outbound

This paper cites Dynamic movement primitives in robotics: A tutorial survey,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Dynamic movement primitives in robotics: A tutorial survey,

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:29.571907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:29.571907Z digest=sha256:4be87ebc16773bc98ac0de5e37240a26febc06e5b162327a43066f8165388c99

Observation ee8585f3-7a79-47e3-997e-c45826390cd3 · outbound

This paper cites Probabilistic movement primitives,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Probabilistic movement primitives,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:32.985900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:29.656775Z digest=sha256:bc63e0366644bea7b1819585894cdac92e3f9096057a632958f62e32956a5085

Observation 828c0b84-50c8-4611-b4e0-f7cdfde5a8bf · outbound

This paper cites Prodmp: A unified perspective on dynamic and probabilistic move- ment primitives,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Prodmp: A unified perspective on dynamic and probabilistic move- ment primitives,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:29.794186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:29.794186Z digest=sha256:312df90c2579b5381b2047c1c652ef75f6518dc510881310e5303969a893672c

Observation ca74b015-19e8-4212-848f-115f4d5c7298 · outbound

This paper cites Learning table tennis with a mixture of motor primitives,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Learning table tennis with a mixture of motor primitives,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:32.727050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:29.941186Z digest=sha256:717174a342b993910eef41c672ffa26929e5b17f709cf15f26aa294a46c15b9f

Observation f84174ff-b5d3-4a09-98f8-cf654d3b4dfa · outbound

This paper cites Residual learning from demonstration: Adapting dmps for contact-rich manipulation,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Residual learning from demonstration: Adapting dmps for contact-rich manipulation,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:32.532660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:30.058492Z digest=sha256:daba519d68c9b58df93e6049fde8d97343b1e17d913256b83873b0a51aea375c

Observation 7bd44fb3-2d90-4ab9-b78a-53a7556d8720 · outbound

This paper cites Residual Robot Learning for Object-Centric Probabilistic Movement Primitives.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Residual Robot Learning for Object-Centric Probabilistic Movement Primitives

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:30.165854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:30.165854Z digest=sha256:3a5d3b1c331f3953e3722310265d050ef6c5d04cd27693ede3b6836600baa5be

Observation a33ad91e-5220-4e9c-acb6-1e5527efa933 · outbound

This paper cites Optimizing robot striking movement primitives with iterative learning control,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Optimizing robot striking movement primitives with iterative learning control,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:32.249735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:30.241146Z digest=sha256:6929a9a17e08107b61c0795412e0eaa17d9abae0de35013e20c3a3ecb2058a56

Observation c58ef950-819b-49cc-8cb6-ace9411fdcde · outbound

This paper cites HuB: Learning Extreme Humanoid Balance.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials HuB: Learning Extreme Humanoid Balance

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:30.356430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:30.356430Z digest=sha256:4cf73c9674c75e0d290dcb8d28e2a686f341a5e4eb04066eebdb3486186087db

Observation bb115905-d894-472a-80c0-0855f0f53da1 · outbound

This paper cites Serl: A software suite for sample- efficient robotic reinforcement learning,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Serl: A software suite for sample- efficient robotic reinforcement learning,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:32.053382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:30.444239Z digest=sha256:3c0e3422f7093518a4f0dd869b8586b6bd2c84f50c1ec4623c330d2cc5d52717

Observation 216a3b5f-2cca-4dda-a44d-aae64872c4a7 · outbound

This paper cites Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:30.534038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:30.534038Z digest=sha256:0f7608514abbe4f682e20790b7b4f4c901db58933a4c16897685fc1af7f8da1f

Observation 6deab804-ea55-4a5f-b512-96f082ec0cb2 · outbound

This paper cites Asap: Aligning simulation and real-world physics for learning agile humanoid whole-body skills,.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials Asap: Aligning simulation and real-world physics for learning agile humanoid whole-body skills,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:31.847434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T13:26:30.680147Z digest=sha256:553907753c2e04a03fbf0160c5fd9bf3c279965c9de05a81bfcdd676d653310f

Observation 6f8bc91c-4f66-4844-b669-7a3a93dcb7f4 · outbound

This paper cites GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning.

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:30.721159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:30.721159Z digest=sha256:c87a5abbf444bcccd86da077149f27f2adbd9046f3f8255b04f5a92882c54dda

Pith citing papers

No inbound Pith citation observations are available.