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Paper Citation Record · LEDGER

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why

As of 9 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2507.05906.

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

pith.paper-citation-record.v1
2507.05906 v2

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:18:54.517768Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T04:34:13.984085Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T20:03:57.005841Z

Reference resolution

26 of 26 outbound references displayed

  • verified exact1
  • verified fuzzy6
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 78f7d8c8-44a7-44ce-ac2b-74dc7312a657 · outbound

This paper cites GR00T N1: An Open Foundation Model for Generalist Humanoid Robots.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

Reference 1

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source=pdf_text observed=2026-08-06T19:18:51.926310Z digest=sha256:6f56b4b0a9832d848a2bd10fe558364b459e097ffefb165394bd35a5c6d50824

Observation 17a8e0bc-e1c3-4c77-a598-6c6d336dd521 · outbound

This paper cites Expressive Whole-Body Control for Humanoid Robots.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Expressive Whole-Body Control for Humanoid Robots

Reference 3

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source=pdf_text observed=2026-08-06T19:18:52.127077Z digest=sha256:147f968a370c4fb2aed42227c4731f6942adb0bbf79ede90538cdae6b378213b

Observation df15e214-bec4-41c2-b45a-0da2d9be169e · outbound

This paper cites Adversarial motion priors make good substitutes for complex reward functions.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Adversarial motion priors make good substitutes for complex reward functions

Reference 5

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source=pdf_text observed=2026-08-06T19:18:52.402038Z digest=sha256:d35d1162cd6cbad218206e6b35d3821a64aac2b566db54f31cbb1d9f483e15e0

Observation a86fd55a-70e3-4dcb-a61c-938fda9885e8 · outbound

This paper cites HumanPlus: Humanoid Shadowing and Imitation from Humans.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why HumanPlus: Humanoid Shadowing and Imitation from Humans

Reference 7

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source=pdf_text observed=2026-08-06T19:18:52.517566Z digest=sha256:769868ea70c3dad3d01a226da11406d09bfc96b8a4682548e0b533ac1998f0bf

Observation 83c46694-8d4a-42a5-a806-3a1c6b6c48a1 · outbound

This paper cites OmniH2O: Universal and Dexterous Human-to-Humanoid Whole-Body Teleoperation and Learning.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why OmniH2O: Universal and Dexterous Human-to-Humanoid Whole-Body Teleoperation and Learning

Reference 9

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source=pdf_text observed=2026-08-06T19:18:52.707507Z digest=sha256:78e10023d474bd10398dd6e2a74c9693665e11211511c7dba523579f5597ded0

Observation 386d583c-cfbd-4eac-892e-1b69105a76bb · outbound

This paper cites FLD: Fourier Latent Dynamics for Structured Motion Representation and Learning.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why FLD: Fourier Latent Dynamics for Structured Motion Representation and Learning

Reference 11

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source=pdf_text observed=2026-08-06T19:18:52.913989Z digest=sha256:41ffeddfb53f40854552e7a62de9607a0252187f782c307fd1e8850b6e5873a7

Observation d0a1c02c-54a4-4b6e-b3e0-2f8c7b0f289a · outbound

This paper cites AMO: Adaptive Motion Optimization for Hyper-Dexterous Humanoid Whole-Body Control.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why AMO: Adaptive Motion Optimization for Hyper-Dexterous Humanoid Whole-Body Control

Reference 12

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source=pdf_text observed=2026-08-06T19:18:52.976566Z digest=sha256:c39dd21acb41504670f93b43a658fbfcdfa7339012b6845d753b536c7858b6d9

Observation f8a95298-6000-4976-8098-f134c3f9b472 · outbound

This paper cites Universal Humanoid Motion Representations for Physics-Based Control.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Universal Humanoid Motion Representations for Physics-Based Control

Reference 13

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:18:53.102274Z digest=sha256:fe5c6c8bee97cf02e9bca7d1f6c54391fad2c653a149d37d30164469400b498e

Observation fb0c4137-7f63-4c3f-9755-f84c4c7bb89b · outbound

This paper cites Robot motion diffusion model: Motion generation for robotic characters.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Robot motion diffusion model: Motion generation for robotic characters

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:18:56.072929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T19:18:53.221341Z digest=sha256:ea1750881b6b99b52cfd3eb171be5bdc41dc8d3d51e43b9f074c73077e63395f

Observation 8e70168d-3ef1-41a9-b633-a757ec6dd76a · outbound

This paper cites Humanmimic: Learning natural locomotion and transitions for humanoid robot via wasserstein adversarial imitation.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Humanmimic: Learning natural locomotion and transitions for humanoid robot via wasserstein adversarial imitation

Reference 15

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raw_fallback, observed 2026-08-06T19:18:55.875196Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T19:18:53.341105Z digest=sha256:c0d4d02bcd77a847a465325c72cb06d863964553e05de0bd173f30d7b87746b1

Observation 635b1337-f526-4246-8db4-e683ec4e8f58 · outbound

This paper cites Gemini Robotics: Bringing AI into the Physical World.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Gemini Robotics: Bringing AI into the Physical World

Reference 16

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source=pdf_text observed=2026-08-06T19:18:53.437976Z digest=sha256:0574f98e6e595d5d56b99c53d7d450f07a354ef60e5a211abc3dfc95b88bc83e

Observation 1131891a-3967-48dc-aa47-f3b112926be7 · outbound

This paper cites Calm: Conditional adversarial latent models for directable virtual characters.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Calm: Conditional adversarial latent models for directable virtual characters

Reference 17

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raw_fallback, observed 2026-08-06T19:18:55.585414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T19:18:53.579784Z digest=sha256:42cf6af3ce618cd48352ed09e05192a722877c09078403bb9daa884325d6f564

Observation e980b54b-5e91-43e8-8e55-ac43fd647de6 · outbound

This paper cites Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models

Reference 18

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source=pdf_text observed=2026-08-06T19:18:53.672853Z digest=sha256:6756e095b367e575fccfdf4c6724841f9158641270b508945b6685eb5b58e2eb

Observation b0a9d1de-5e81-4f2f-896f-af21b9a32bfa · outbound

This paper cites Advanced skills through multiple adversarial motion priors in reinforcement learning.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Advanced skills through multiple adversarial motion priors in reinforcement learning

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-06T19:18:55.368665Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T19:18:53.756313Z digest=sha256:053f7fc3068a16bfc6bf636fbee6018b288e3da60a24a22f3be7c2b912fd9ced

Observation 955d67a0-f1d1-414c-9066-6923fd04e34d · outbound

This paper cites PhysHOI: Physics-Based Imitation of Dynamic Human-Object Interaction.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why PhysHOI: Physics-Based Imitation of Dynamic Human-Object Interaction

Reference 20

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source=pdf_text observed=2026-08-06T19:18:53.874785Z digest=sha256:ea5627f777e3b44d007e557f5e257c22e0af5a08e581fc272e85b60e017078d1

Observation 87ee40a5-def8-4657-a763-d19581219892 · outbound

This paper cites DFM: Deep Fourier Mimic for Expressive Dance Motion Learning.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why DFM: Deep Fourier Mimic for Expressive Dance Motion Learning

Reference 21

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local_arxiv, observed 2026-08-06T19:18:54.973119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T19:18:53.961622Z digest=sha256:7ac02cf110944723da1d1b68602ce928113c85f9f6357015897f7005ad385366

Observation 759d5763-dc6d-45e1-8d08-2daf502e5380 · outbound

This paper cites Constrained style learning from imperfect demonstrations under task optimality.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Constrained style learning from imperfect demonstrations under task optimality

Reference 22

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source=pdf_text observed=2026-08-06T19:18:54.083832Z digest=sha256:54f4a1a5574a78922a948bee711dff39f05d83737617f0a0c43f7031edeefc79

Observation 523bbea8-b11d-4035-b11c-210afe24f13f · outbound

This paper cites PARC: Physics-based Augmentation with Reinforcement Learning for Character Controllers.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why PARC: Physics-based Augmentation with Reinforcement Learning for Character Controllers

Reference 23

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source=pdf_text observed=2026-08-06T19:18:54.203162Z digest=sha256:dff1683daddce47e8a6cbeada4a7545291836f4c4886e3afdfd8822e1c55d841

Observation ff7ad1ec-9aa1-407f-8bae-21ae6514e74a · outbound

This paper cites RobotKeyframing: Learning Locomotion with High-Level Objectives via Mixture of Dense and Sparse Rewards.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why RobotKeyframing: Learning Locomotion with High-Level Objectives via Mixture of Dense and Sparse Rewards

Reference 24

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source=pdf_text observed=2026-08-06T19:18:54.280656Z digest=sha256:24f36322d2908f89db014799b34bc5f8daab7440ebdb44dd9f403fde5cb886e5

Observation 40f6f89a-c495-4065-9ffa-008dabe93cef · outbound

This paper cites TWIST: Teleoperated Whole-Body Imitation System.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why TWIST: Teleoperated Whole-Body Imitation System

Reference 25

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source=pdf_text observed=2026-08-06T19:18:54.405583Z digest=sha256:34fb266f7384e1b1f5dc5dec7bcb73a9a862d0491e484db43c8882925c19342c

Observation 52d81f56-30d7-45f7-a89f-109813f3f07d · outbound

This paper cites Motion Priors Reimagined: Adapting Flat-Terrain Skills for Complex Quadruped Mobility.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Motion Priors Reimagined: Adapting Flat-Terrain Skills for Complex Quadruped Mobility

Reference 26

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source=pdf_text observed=2026-08-06T19:18:54.517768Z digest=sha256:70e56136769f873fe1accb536fff78e5f5e8d476ba14911cedca50b632d220ba

Observation 844e5394-9e86-497f-b5c3-3a54fa9a53ed · outbound

This paper cites ExBody2: Advanced Expressive Humanoid Whole-Body Control.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why ExBody2: Advanced Expressive Humanoid Whole-Body Control

Reference 2016

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source=pdf_text observed=2026-08-06T19:18:52.764263Z digest=sha256:3798c17f9f6673984f31e163a8d01c90cc6888f731b33c1106b9fdc4b6c22402

Observation 78f15a55-3cca-411c-a37e-65dca7ea0750 · outbound

This paper cites DreamPolicy: A Unified World-model Policy for Scalable Humanoid Locomotion.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why DreamPolicy: A Unified World-model Policy for Scalable Humanoid Locomotion

Reference 2022

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source=pdf_text observed=2026-08-06T19:18:52.486220Z digest=sha256:4bd629b533176c9f7d926ee259ff8bb9fcda7c2f259d45929fa7854482dfebc6

Observation 88c0512d-09ef-4fc3-b087-89f5476a4de7 · outbound

This paper cites C · ase: Learning conditional adversarial skill embeddings for physics-based characters.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why C · ase: Learning conditional adversarial skill embeddings for physics-based characters

Reference 2023

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raw_fallback, observed 2026-08-06T19:18:56.426847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T19:18:52.300885Z digest=sha256:091c6669a0f005765d055b5fd2ddf2f2c93d246cb1d63c63cb041a1f3942adab

Observation 8024055a-1385-4016-a820-2c43c255c350 · outbound

This paper cites Syn- thesizing physical character-scene interactions.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why Syn- thesizing physical character-scene interactions

Reference 2024

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raw_fallback, observed 2026-08-06T19:18:56.250035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T19:18:52.604697Z digest=sha256:66b67437c7eca2ba478bba51fed50c6857b50e8ad6cd79f97199edcff79bc87a

Observation 2f6e7ff2-e66b-4236-a3b3-f7c4b005d476 · outbound

This paper cites GMT: General Motion Tracking for Humanoid Whole-Body Control.

Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why GMT: General Motion Tracking for Humanoid Whole-Body Control

Reference 2025

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source=pdf_text observed=2026-08-06T19:18:52.011627Z digest=sha256:448912a118cde17530882a97d6ebbebd17301206d6728be52f262765afe10d92

Pith citing papers

Observation 1b17122b-c670-4a0c-beb1-7db4f355df2f · inbound

Booster Lab: A Data-Centric Pipeline for Learning Deployable Humanoid Locomotion Policies cites this paper.

Booster Lab: A Data-Centric Pipeline for Learning Deployable Humanoid Locomotion Policies Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why

Reference 15

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arxiv_id, observed 2026-06-29T20:03:57.010556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T04:34:13.984085Z digest=sha256:dc0d8120332f6512f01ae855c31160476b7ce67d4c4bb79e93227bbf9d8f8c4f