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Paper Citation Record · LEDGER

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

As of 18 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 2026-08-18T06:34:40.430872+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=sha256:77235eb26d57ffc69484f15f81c7f28408601b752babe25cb44556c65bead2f4

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=sha256:33aeaf34beda86c6b5acbe576378e098c85e58e739ebd079a34b1e2e6375a26a

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:18:52.707507Z digest=sha256:b18c2183052a3e91c568a7ecb55cb97a38fce66b551f122c23106e8e775588c2

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=sha256:69349c392df8cdc96afed4792fd77566f3343d3b6f42cc9aed8aca27bafce96e

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:18:52.976566Z digest=sha256:4a031f7d6567fee99258c0c5aa9bb2725448a43970b4c8d5047f3b3a10ab3263

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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source=pdf_text observed=2026-08-06T19:18:53.102274Z digest=sha256:bfc2c4da0ecec747c23854bb72535900eab150a5606bd8cbca8d5e869b3d3178

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:18:53.221341Z digest=sha256:f7db434b302f73145e1dc0c73115143da842386d012283d0914e766dfa7234ca

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

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=2026-08-06T19:18:53.341105Z digest=sha256:c92cc6836463877c6431a4b2a46a5199909a6f5aa94d5a25b1bc219a12617f50

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=sha256:6b44268a8ca15a2d9fbeb8000162bcb73d8e8adbe32c7c1e331fd98bd5a57012

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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verified fuzzy
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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:18:53.579784Z digest=sha256:358fe25332e90085f83cd68d8e4e7c958abfa76f9bf24f303568394f32dc02e3

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:b5cbd8ab8b16fe81f891dbc4b5eba62f1be60ccb41454abd5b786f4f4feae4ed

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

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=2026-08-06T19:18:53.756313Z digest=sha256:e441c5305923324a09129297c344c4d3601133b67c5de87a3216c58920eb5fc7

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=sha256:7cb20b02d8e7cf008c89c29e84c8f12885b939f73dd0c23f87802f5d74075d60

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:18:53.961622Z digest=sha256:887a68fd3613029262ed85183c412755492718478f5926e03226676fa140f568

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:b377eb88667b2a600f3e7a841bfb21272a0ea05d94f113354c7e9abce77ec397

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=sha256:4365a2501879aad660f166395827c5efe685ab8a22a0afaea04695fe04d3df9d

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:f1aec60065f6a57f75b3f0f7ed01daa2bf53493861f0be4d64b37c1b2a9b9830

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=sha256:356b0a5137a6d8e63880d7065940f505fad3e123fffe93e4f3c689b36c1398b4

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=sha256:233bfd79d3ef5aecfaba63f45ca0df633d1789056462a78a971d60727ada0cb2

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=sha256:316093cf1e650ec55d9f45b16c4f210e689a5b4ba8acf11b9ec190400d837c75

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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verified fuzzy
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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:18:52.300885Z digest=sha256:e4aa6f1bbf7ba831d2d741ae58bb0aa79128011476787b324cc8c68617275f11

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:18:52.604697Z digest=sha256:b2c805d996aebeb1c73628f71f1c1763aa912ce11351e49a250a7d92a1fc3f37

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=sha256:4fc75cca7664d94bee66e374ad412ae003827b78fa90d8c44c63d5ad0b8cdfdb

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-29T04:34:13.984085Z digest=sha256:98a7d1e5d4d85bb8d94b8c7aea745c3e549ec50fa33523f5e9270178720903f8