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Paper Citation Record · LEDGER

Learning to Explore in Motion and Interaction Tasks

As of 22 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:1908.03731.

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

pith.paper-citation-record.v1
1908.03731 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:09:48.234525Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

21 of 21 outbound references displayed

  • verified exact1
  • verified fuzzy5
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aec774ad-f1d2-4670-ad1f-c6a97b4bdb26 · outbound

This paper cites Learning agile and dynamic motor skills for legged robots,.

Learning to Explore in Motion and Interaction Tasks Learning agile and dynamic motor skills for legged robots,

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.089790Z digest=sha256:2d4136e68419ec8de2eb8a2551d8eaa1b3fe204b526d406e9a195267cb908c94

Observation ccbc2481-b431-4fa5-9833-7d82bedfaaac · outbound

This paper cites Control policy with autocorrelated noise in reinforce- ment learning for robotics,.

Learning to Explore in Motion and Interaction Tasks Control policy with autocorrelated noise in reinforce- ment learning for robotics,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-14T14:09:49.059163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T14:09:48.096430Z digest=sha256:5f792e5dd7dd26cdaa94f259e12d8034767fdc266ce768a40efdb14a2bbebd67

Observation aa12f0c4-6bb8-40f5-a2be-1c98e1ff98e7 · outbound

This paper cites On the theory of the brownian motion,.

Learning to Explore in Motion and Interaction Tasks On the theory of the brownian motion,

Reference 3

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no resolver link, observed 2026-08-14T14:09:48.102370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.102370Z digest=sha256:6cf6062cea1d4a81b37d1524c5818be6b70cc5cd94ba14d7766ff3e2c37fdaaf

Observation 361dba91-4bb8-42fb-b6a3-7c03394e203b · outbound

This paper cites Continuous control with deep reinforcement learning.

Learning to Explore in Motion and Interaction Tasks Continuous control with deep reinforcement learning

Reference 4

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no resolver link, observed 2026-08-14T14:09:48.109408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.109408Z digest=sha256:08f5a874524c1de00553672165bade18997034bf9b5f2a36158bcce583fe884c

Observation 9cfe1b93-4855-4d3b-ad86-3898b9d37e77 · outbound

This paper cites Parameter Space Noise for Exploration.

Learning to Explore in Motion and Interaction Tasks Parameter Space Noise for Exploration

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-14T14:09:48.115876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.115876Z digest=sha256:a55f39b4741abe79cdd2b3487b358c1a595dabec27917d49241b72c28ce7721f

Observation 9d0daaf7-f1ff-4b8c-bf3e-70021507c8c2 · outbound

This paper cites Intrinsically motivated learning of hierarchical collec- tions of skills,.

Learning to Explore in Motion and Interaction Tasks Intrinsically motivated learning of hierarchical collec- tions of skills,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:09:48.962663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T14:09:48.121895Z digest=sha256:7b6ce0185134de91c7a163823812df3adcf07f5a1c03d27f4e3c33f85a914c97

Observation 5b329568-4d02-4138-8639-44a256133d50 · outbound

This paper cites Curiosity Driven Exploration of Learned Disentangled Goal Spaces.

Learning to Explore in Motion and Interaction Tasks Curiosity Driven Exploration of Learned Disentangled Goal Spaces

Reference 7

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unresolved
no resolver link, observed 2026-08-14T14:09:48.128971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.128971Z digest=sha256:e979a58f4227140fe12d8ece847f93c46d5784911a92ac14dbda7bb5b1c43ba2

Observation e6173d78-581d-4cd4-ae32-f45d659c805a · outbound

This paper cites Curiosity-Driven Exploration by Self-Supervised Prediction,.

Learning to Explore in Motion and Interaction Tasks Curiosity-Driven Exploration by Self-Supervised Prediction,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:09:48.868708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T14:09:48.134153Z digest=sha256:999273f64b8702e1b094dbadbe42f2845448ff2cc01fba42549c3d33eaae44f9

Observation 2d655ec1-5006-41a3-b5cb-5c1f1bbebb95 · outbound

This paper cites Distral: Robust Multitask Reinforcement Learning.

Learning to Explore in Motion and Interaction Tasks Distral: Robust Multitask Reinforcement Learning

Reference 9

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no resolver link, observed 2026-08-14T14:09:48.139755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.139755Z digest=sha256:eda9e46a447888f09918654323253701a5610d03a95aa2223354ca39e945657d

Observation b0eef75f-bc94-4b84-a962-46fa1321384e · outbound

This paper cites Learning and Transfer of Modulated Locomotor Controllers.

Learning to Explore in Motion and Interaction Tasks Learning and Transfer of Modulated Locomotor Controllers

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-14T14:09:48.145640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.145640Z digest=sha256:a7578d1876ef3d99e187fe7b5e6661786c4f96e61c0d038640473a935e9e4ce8

Observation 9d5967b7-b026-4170-b923-8a5e02b2f11d · outbound

This paper cites Learning by Playing - Solving Sparse Reward Tasks from Scratch.

Learning to Explore in Motion and Interaction Tasks Learning by Playing - Solving Sparse Reward Tasks from Scratch

Reference 11

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unresolved
no resolver link, observed 2026-08-14T14:09:48.151898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.151898Z digest=sha256:12b060b989c664ab9aec4b12ef46e1d2694a2422ec9765bc3fc8109bb1513180

Observation 817f538d-3f34-4bf8-942f-48bccf1c7d74 · outbound

This paper cites Dynamic movement primitives-a framework for motor control in humans and humanoid robotics,.

Learning to Explore in Motion and Interaction Tasks Dynamic movement primitives-a framework for motor control in humans and humanoid robotics,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-14T14:09:48.159765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.159765Z digest=sha256:b0106f36c15638500daa9888bfe1aaef7b95103f6daffee4eeb99abedb981058

Observation c6d48416-552e-4505-a902-2b94d166fa71 · outbound

This paper cites Dynamical movement primitives: learning attractor models for motor behaviors,.

Learning to Explore in Motion and Interaction Tasks Dynamical movement primitives: learning attractor models for motor behaviors,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T14:09:48.164883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.164883Z digest=sha256:2b0200e49e2b0982f7cadba75e8ad92b5ab45b8b2e9fb0d77c8eb70908f51a9b

Observation df4c8837-6f04-4fc9-9d75-31873d66e698 · outbound

This paper cites Long short-term memory,.

Learning to Explore in Motion and Interaction Tasks Long short-term memory,

Reference 14

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unresolved
no resolver link, observed 2026-08-14T14:09:48.171347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.171347Z digest=sha256:adf1996a228279a3ddd73e3d57c86bf3bb720c2919458bf2fc3dab9ade99a3fe

Observation c5b94969-d911-48bf-bdd3-db93190fa2f8 · outbound

This paper cites Contact-Invariant Opti- mization for Hand Manipulation,.

Learning to Explore in Motion and Interaction Tasks Contact-Invariant Opti- mization for Hand Manipulation,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:09:48.742800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T14:09:48.176615Z digest=sha256:5e315b5c2366ebe26e942bfd61a00aba5605d73a562c487a7ce6fa954b106fa4

Observation ef3cbebb-2a5e-465f-8a30-8d1f356d829b · outbound

This paper cites On Time Optimization of Centroidal Momentum Dynamics.

Learning to Explore in Motion and Interaction Tasks On Time Optimization of Centroidal Momentum Dynamics

Reference 16

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verified exact
local_arxiv, observed 2026-08-14T14:09:48.413605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T14:09:48.182020Z digest=sha256:a9c6367d0a8283b4015e5409ef6c8fb54ab23b03d4cd5e58981cc049e647b4ef

Observation 1babd8d1-e38b-4a5c-a115-9cfc69df2d90 · outbound

This paper cites Robot program- ming by demonstration,.

Learning to Explore in Motion and Interaction Tasks Robot program- ming by demonstration,

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.187921Z digest=sha256:78e337ab792c5a5280e361652d1542a3a93443fecf4b97b82f819f4cea7161a8

Observation f98a0b4a-0bc1-4941-b7e6-4da40396b0ff · outbound

This paper cites Generating Sequences With Recurrent Neural Networks.

Learning to Explore in Motion and Interaction Tasks Generating Sequences With Recurrent Neural Networks

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.194139Z digest=sha256:d0b44b81385d83eaf4a9186b09fd949750bf61a3a84f22e88018fa87296d23f1

Observation 69afdd9c-62b5-4399-8e7c-1e51cffab150 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Learning to Explore in Motion and Interaction Tasks Proximal Policy Optimization Algorithms

Reference 19

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source=pdf_text observed=2026-08-14T14:09:48.203224Z digest=sha256:c95ea3546abc1610be3a9aab3d7aa14c2506542a19f3699cc629435f4dc5eb78

Observation 02e7ae39-a459-4c50-a7a1-e9ba3b904322 · outbound

This paper cites Openai baselines,.

Learning to Explore in Motion and Interaction Tasks Openai baselines,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:09:48.642004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T14:09:48.215493Z digest=sha256:281069d04da258dcdf2f67ff733f05a593bfb004806c6b849cfcef6f1908b532

Observation 61004ed7-1079-4302-87b0-c13f14c8a04c · outbound

This paper cites How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments.

Learning to Explore in Motion and Interaction Tasks How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:09:48.234525Z digest=sha256:9574dc8d7036c4da97b939db9e637b64f17b3f3e850c5bf69d8eead233645a07

Pith citing papers

No inbound Pith citation observations are available.