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Paper Citation Record · LEDGER

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running

As of 21 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2508.03070.

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

pith.paper-citation-record.v1
2508.03070 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:45:20.616538Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:31:07.390392Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

23 of 23 outbound references displayed

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Outbound references

Observation 751a421d-9e6d-49d8-81be-e9ab6949ff24 · outbound

This paper cites Reinforcement learning for robust parameterized locomotion control of bipedal robots,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Reinforcement learning for robust parameterized locomotion control of bipedal robots,

Reference 1

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source=pdf_text observed=2026-08-06T04:45:18.770861Z digest=sha256:b8d547e7d8ef746c4ebe363b0d6bccf686982031ed2a57fdc315962e690c09d6

Observation cbf4e9e1-c001-4806-88b3-6c65ac43e7a6 · outbound

This paper cites Reinforcement learning-based cascade motion policy design for robust 3d bipedal locomotion,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Reinforcement learning-based cascade motion policy design for robust 3d bipedal locomotion,

Reference 2

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source=pdf_text observed=2026-08-06T04:45:18.829994Z digest=sha256:09acd3a586e88bcadb08fea9c983c50d20093cb2af12b80dda0fa7d3a30f2d04

Observation f916aa11-0cfd-4c15-9528-a96cc3004812 · outbound

This paper cites Learning bipedal robot locomotion from human movement,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Learning bipedal robot locomotion from human movement,

Reference 3

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source=pdf_text observed=2026-08-06T04:45:18.924473Z digest=sha256:52c46fb19f646855faf979a0c292bfed30a924e2b8619d4a8ded63df15797506

Observation 68498159-bdc9-46a3-90f3-720336eec7ca · outbound

This paper cites Sim- to-Real Learning of All Common Bipedal Gaits via Periodic Reward Composition,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Sim- to-Real Learning of All Common Bipedal Gaits via Periodic Reward Composition,

Reference 4

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source=pdf_text observed=2026-08-06T04:45:18.986128Z digest=sha256:75503a4b96b1d866f92ddafa097e693a583370e74eb79bfa66916abfc4038133

Observation 663db34b-5383-441e-891b-993c9ae4aa11 · outbound

This paper cites Blind Bipedal Stair Traversal via Sim-to-Real Reinforcement Learning.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Blind Bipedal Stair Traversal via Sim-to-Real Reinforcement Learning

Reference 5

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source=pdf_text observed=2026-08-06T04:45:19.085426Z digest=sha256:226079881c07028b17cce3e9b3db31c735fe10169f3ae79940b2bba49d64153f

Observation 1086895b-724c-4ff2-9978-b2904c86319d · outbound

This paper cites Sim- to-real learning for bipedal locomotion under unsensed dynamic loads,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Sim- to-real learning for bipedal locomotion under unsensed dynamic loads,

Reference 6

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source=pdf_text observed=2026-08-06T04:45:19.168942Z digest=sha256:249f4f3eabeadc4687dc2839e4c2256e285683ed8e06558e08ca3e41a89e703d

Observation 362c75fc-22d5-4c27-b1da-d15b2aff23cf · outbound

This paper cites Challenges of Learned High- Speed Locomotion over Five Kilometers in the Real World,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Challenges of Learned High- Speed Locomotion over Five Kilometers in the Real World,

Reference 7

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source=pdf_text observed=2026-08-06T04:45:19.253128Z digest=sha256:12d7a17271cca86c4cd81eaaeb960cb102d7c3fa961fd0aaccde1d33240ed91f

Observation 548b13c2-0ec0-4d6c-ba89-7c228cf74d44 · outbound

This paper cites Fastrunner: A fast, efficient and robust bipedal robot. concept and planar simulation,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Fastrunner: A fast, efficient and robust bipedal robot. concept and planar simulation,

Reference 8

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source=pdf_text observed=2026-08-06T04:45:19.339162Z digest=sha256:6d4f9591ccaa877505e878a4198b2f46d4383de37433ce5eb9813af1531c3fc8

Observation ef99c02e-62bb-429f-92ff-95bb154f440d · outbound

This paper cites Robust spring mass model running for a physical bipedal robot,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Robust spring mass model running for a physical bipedal robot,

Reference 9

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source=pdf_text observed=2026-08-06T04:45:19.460658Z digest=sha256:d1d9a59b8b99a1cb5ed71e19f84970f9eb53cd1737774e66f205c9c76929b21e

Observation 69bfec24-ecbf-4ea9-b7eb-efcbb8239beb · outbound

This paper cites Bipedal robotic running with durus- 2d: Bridging the gap between theory and experiment,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Bipedal robotic running with durus- 2d: Bridging the gap between theory and experiment,

Reference 10

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Observation 1aa9281f-a00f-4294-9fbb-02ef7c4094a3 · outbound

This paper cites Practical Reinforcement Learning for Bipedal Locomotion,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Practical Reinforcement Learning for Bipedal Locomotion,

Reference 11

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source=pdf_text observed=2026-08-06T04:45:19.656505Z digest=sha256:58d5fe6bbd641e9c0f94e64ba229fe06018311a3552137d3cc08605d3f20a1f7

Observation 3960521c-81c7-4a36-83e9-9aadd563d31d · outbound

This paper cites Learning loco- motion skills using deeprl: Does the choice of ac- tion space matter?.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Learning loco- motion skills using deeprl: Does the choice of ac- tion space matter?

Reference 12

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Observation ef0a07ec-e370-4eaa-a764-ffbdb8c402ed · outbound

This paper cites Feedback control for cassie with deep rein- forcement learning,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Feedback control for cassie with deep rein- forcement learning,

Reference 13

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Observation b0b3c2e4-62cf-4d3f-97c0-e502985f9a35 · outbound

This paper cites Sim- to-real: Learning agile locomotion for quadruped robots,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Sim- to-real: Learning agile locomotion for quadruped robots,

Reference 14

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source=pdf_text observed=2026-08-06T04:45:19.895382Z digest=sha256:19ec978a752de7e3bb8a8b8b86ead488e2b68888f0f1e24d511c6ab8c8fb11e6

Observation a92cc94c-9f9f-4c1c-a577-a47cb468e542 · outbound

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

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Learning agile and dynamic motor skills for legged robots,

Reference 15

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source=pdf_text observed=2026-08-06T04:45:19.992125Z digest=sha256:f1035cba89d39fbac68115705060e4a4845d9ca9e1a164f2dd5f45e730c744e9

Observation 7d3e40f2-a816-4939-a65d-eacf1baca31a · outbound

This paper cites Deepgait: Planning and control of quadrupedal gaits using deep reinforcement learning,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Deepgait: Planning and control of quadrupedal gaits using deep reinforcement learning,

Reference 16

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Observation 4019977b-6908-4c7c-9990-3bc817077b5a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Proximal Policy Optimization Algorithms

Reference 17

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source=pdf_text observed=2026-08-06T04:45:20.158514Z digest=sha256:b4ad15fe095b13bb7e7bd0fdf62871b94e06aee4677fd7144f9c32422588097b

Observation 3ca098e4-ea63-455d-9a73-e814249b0abe · outbound

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

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running MuJoCo: A physics engine for model-based control,

Reference 18

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source=pdf_text observed=2026-08-06T04:45:20.220828Z digest=sha256:b5cad40ee7c3b1213d6e5cef4c994946eeb1915df57bbdc1ed7dd71de7466099

Observation d3ff527d-bb8c-4d98-9caa-c17d080b283b · outbound

This paper cites Learning memory-based control for human-scale bipedal locomotion,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Learning memory-based control for human-scale bipedal locomotion,

Reference 19

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Observation 427654d6-debe-4611-b035-287a6943b86d · outbound

This paper cites Learning quadrupedal locomotion over challenging terrain,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Learning quadrupedal locomotion over challenging terrain,

Reference 20

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source=pdf_text observed=2026-08-06T04:45:20.358116Z digest=sha256:b6b94390794e2037754a6ab5656ede1a1e8a42fbd58fe3b0701991fb876c91c7

Observation a986a28a-b9ef-4b8c-bda8-ab8631e92db5 · outbound

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

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Sim-to-real transfer of robotic control with dynamics randomization,

Reference 21

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Observation 3d51028f-f1bb-49d3-b814-3e3a135966a4 · outbound

This paper cites Fast and efficient locomotion via learned gait tran- sitions,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Fast and efficient locomotion via learned gait tran- sitions,

Reference 22

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Observation 7b34f067-7d17-4f0d-92c1-591c54cdd0e0 · outbound

This paper cites Faster top running speeds are achieved with greater ground forces not more rapid leg movements,.

Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running Faster top running speeds are achieved with greater ground forces not more rapid leg movements,

Reference 23

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Pith citing papers

Observation d78ead42-311a-493f-a7fe-b0166595866f · inbound

CBF-RL: Safety Filtering Reinforcement Learning in Training with Control Barrier Functions cites this paper.

CBF-RL: Safety Filtering Reinforcement Learning in Training with Control Barrier Functions Optimizing Bipedal Locomotion for The 100m Dash With Comparison to Human Running

Reference 1

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source=pdf_text observed=2026-08-04T09:31:07.390392Z digest=sha256:7f69e69b2eb39610d1bb4f6d203553fbe165b43b2fc82da555b37489398752ec