Paper Citation Record · LEDGER

LS-GAN: Human Motion Synthesis with Latent-space GANs

As of 14 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2501.01449.

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

pith.paper-citation-record.v1
2501.01449 v1

Coverage vector

measured 55 of 55 reference resolution

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measured 56 of 56 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:06:31.257017Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

55 of 55 outbound references displayed

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verified fuzzy39
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5cbde967-8bab-4ba9-98c1-3d232f559bde · outbound

This paper cites Text2action: Generative adversarial synthesis from language to action.

LS-GAN: Human Motion Synthesis with Latent-space GANs Text2action: Generative adversarial synthesis from language to action

Reference 1

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Observation d6852584-fc00-458c-acef-732f153851cb · outbound

This paper cites Lan- guage2pose: Natural language grounded pose forecasting.

LS-GAN: Human Motion Synthesis with Latent-space GANs Lan- guage2pose: Natural language grounded pose forecasting

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:12.045132Z

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Observation ff188f66-11ef-4c0e-8faf-b3d5f5e04e33 · outbound

This paper cites Lan- guage2pose: Natural language grounded pose forecasting.

LS-GAN: Human Motion Synthesis with Latent-space GANs Lan- guage2pose: Natural language grounded pose forecasting

Reference 3

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Observation 9fbe6cf2-8509-4691-b171-b22c16691152 · outbound

This paper cites Wasserstein gan, 2017.

LS-GAN: Human Motion Synthesis with Latent-space GANs Wasserstein gan, 2017

Reference 4

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Observation 84e421b2-575b-4c10-a1b3-1cfe9e0c4aa5 · outbound

This paper cites Text2gestures: A transformer-based network for generating emotive body gestures for virtual agents.

LS-GAN: Human Motion Synthesis with Latent-space GANs Text2gestures: A transformer-based network for generating emotive body gestures for virtual agents

Reference 5

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Observation 78837075-95f0-416b-9702-48c52756bc5c · outbound

This paper cites Implicit neural representations for variable length human motion generation.

LS-GAN: Human Motion Synthesis with Latent-space GANs Implicit neural representations for variable length human motion generation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.987191Z

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Observation ec87e671-b44f-4e08-9cf0-f8d66826a16a · outbound

This paper cites Executing your commands via motion diffusion in latent space, 2023.

LS-GAN: Human Motion Synthesis with Latent-space GANs Executing your commands via motion diffusion in latent space, 2023

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.971704Z

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Observation c526bbfd-3f64-44e3-a27f-21121e3f285f · outbound

This paper cites an unresolved cited work.

LS-GAN: Human Motion Synthesis with Latent-space GANs Unresolved cited work

Reference 8

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Observation 34567a25-44e8-4ffb-8f7b-26230260a63b · outbound

This paper cites Synthesis of compositional animations from textual descriptions.

LS-GAN: Human Motion Synthesis with Latent-space GANs Synthesis of compositional animations from textual descriptions

Reference 9

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Observation d51f55db-253d-43c3-812f-8015428c29b6 · outbound

This paper cites Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio.

LS-GAN: Human Motion Synthesis with Latent-space GANs Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio

Reference 10

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Observation 933daf29-7e5a-4788-bcdc-47017462d9ec · outbound

This paper cites Improved training of wasserstein gans, 2017.

LS-GAN: Human Motion Synthesis with Latent-space GANs Improved training of wasserstein gans, 2017

Reference 11

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Observation cb024db1-24e9-469d-9bc5-a832c373eb47 · outbound

This paper cites TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts.

LS-GAN: Human Motion Synthesis with Latent-space GANs TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts

Reference 12

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Observation e63082f1-e659-4f50-94c5-cd8f2b93e4b6 · outbound

This paper cites Generating diverse and natural 3d human motions from text.

LS-GAN: Human Motion Synthesis with Latent-space GANs Generating diverse and natural 3d human motions from text

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.901114Z

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Observation c970a29c-b6fb-42f6-a934-6c7b840caec4 · outbound

This paper cites Generating diverse and natural 3d human motions from text.

LS-GAN: Human Motion Synthesis with Latent-space GANs Generating diverse and natural 3d human motions from text

Reference 14

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Observation 792d8f80-a761-47e6-b647-9915b3d1c009 · outbound

This paper cites Generating diverse and natural 3d human motions from text.

LS-GAN: Human Motion Synthesis with Latent-space GANs Generating diverse and natural 3d human motions from text

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.872375Z

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Observation 224c31f3-80a2-44a2-8b03-6e6196d9de46 · outbound

This paper cites Ac- tion2motion: Conditioned generation of 3d human motions.

LS-GAN: Human Motion Synthesis with Latent-space GANs Ac- tion2motion: Conditioned generation of 3d human motions

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.857666Z

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Observation df8c1a2e-234e-4972-892a-83df38bc035d · outbound

This paper cites Deep residual learning for image recognition, 2015.

LS-GAN: Human Motion Synthesis with Latent-space GANs Deep residual learning for image recognition, 2015

Reference 17

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Observation b9b16d98-5f18-4819-96aa-961ca8ae9bd5 · outbound

This paper cites Denoising diffu- sion probabilistic models, 2020.

LS-GAN: Human Motion Synthesis with Latent-space GANs Denoising diffu- sion probabilistic models, 2020

Reference 18

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Observation 91002c56-a7ae-407a-a34a-c769f2d40807 · outbound

This paper cites Motiongpt: Human motion as a foreign language,.

LS-GAN: Human Motion Synthesis with Latent-space GANs Motiongpt: Human motion as a foreign language,

Reference 19

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Observation 03442d09-cdf6-4491-b715-65766529e6b9 · outbound

This paper cites Scaling up gans for text-to-image synthesis, 2023.

LS-GAN: Human Motion Synthesis with Latent-space GANs Scaling up gans for text-to-image synthesis, 2023

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.810325Z

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Observation 6569aea6-76f1-4731-95a9-aa0d79399e79 · outbound

This paper cites Audio-driven facial animation by joint end- to-end learning of pose and emotion.

LS-GAN: Human Motion Synthesis with Latent-space GANs Audio-driven facial animation by joint end- to-end learning of pose and emotion

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.796323Z

Source-reported events for the cited work

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Observation ae1057f5-e1f7-453f-91ab-22b8522a3d02 · outbound

This paper cites A style-based generator architecture for generative adversarial networks,.

LS-GAN: Human Motion Synthesis with Latent-space GANs A style-based generator architecture for generative adversarial networks,

Reference 22

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Observation 47bd66a8-9da9-4822-91b6-220d864223d1 · outbound

This paper cites Flame: Free- form language-based motion synthesis & editing.

LS-GAN: Human Motion Synthesis with Latent-space GANs Flame: Free- form language-based motion synthesis & editing

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.772647Z

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Observation 38239968-1167-4434-bc7b-386b61aa87d0 · outbound

This paper cites Flame: Free- form language-based motion synthesis & editing, 2023.

LS-GAN: Human Motion Synthesis with Latent-space GANs Flame: Free- form language-based motion synthesis & editing, 2023

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.758158Z

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Observation 174a2ce8-b7db-430a-a7f6-9c59fa0ed72d · outbound

This paper cites Dance- former: Music conditioned 3d dance generation with para- metric motion transformer.

LS-GAN: Human Motion Synthesis with Latent-space GANs Dance- former: Music conditioned 3d dance generation with para- metric motion transformer

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.743170Z

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Observation a4a39087-b791-4d73-be48-dd443a42474d · outbound

This paper cites Ganimator: neural motion synthesis from a single sequence.

LS-GAN: Human Motion Synthesis with Latent-space GANs Ganimator: neural motion synthesis from a single sequence

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.728636Z

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Observation 00aa1534-418d-47f5-b27b-da40670b21ee · outbound

This paper cites Ross, and Angjoo Kanazawa.

LS-GAN: Human Motion Synthesis with Latent-space GANs Ross, and Angjoo Kanazawa

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.714308Z

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Observation 441661c2-4563-42dd-88f0-8eaf52579a67 · outbound

This paper cites Ross, and Angjoo Kanazawa.

LS-GAN: Human Motion Synthesis with Latent-space GANs Ross, and Angjoo Kanazawa

Reference 28

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Observation e2cee6eb-c34d-4685-b056-6c8f905319cd · outbound

This paper cites Piano: A parametric hand bone model from magnetic reso- nance imaging.

LS-GAN: Human Motion Synthesis with Latent-space GANs Piano: A parametric hand bone model from magnetic reso- nance imaging

Reference 29

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Observation 2663c723-235f-48fc-bf7d-bab013876ca1 · outbound

This paper cites A comprehensive survey on knowledge distil- lation of diffusion models, 2023.

LS-GAN: Human Motion Synthesis with Latent-space GANs A comprehensive survey on knowledge distil- lation of diffusion models, 2023

Reference 30

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Observation 5af40e99-5c23-4948-bb7f-b085ca5ef62f · outbound

This paper cites Troje, Ger- ard Pons-Moll, and Michael J.

LS-GAN: Human Motion Synthesis with Latent-space GANs Troje, Ger- ard Pons-Moll, and Michael J

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.655106Z

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Observation b6ee7aac-af6b-40c9-bdad-426f63fe7688 · outbound

This paper cites Conditional generative adversarial nets, 2014.

LS-GAN: Human Motion Synthesis with Latent-space GANs Conditional generative adversarial nets, 2014

Reference 32

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Observation 49173bec-270b-42e8-beb3-dd4ff655c29a · outbound

This paper cites Black, and G ¨ul Varol.

LS-GAN: Human Motion Synthesis with Latent-space GANs Black, and G ¨ul Varol

Reference 33

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Observation 052481f5-17f9-4ee9-8582-121e999a63a9 · outbound

This paper cites TEMOS: Generating diverse human motions from textual descriptions.

LS-GAN: Human Motion Synthesis with Latent-space GANs TEMOS: Generating diverse human motions from textual descriptions

Reference 34

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Observation 0f5bfeec-8a41-40b1-bdd2-dc383226b14f · outbound

This paper cites Black, and G ¨ul Varol.

LS-GAN: Human Motion Synthesis with Latent-space GANs Black, and G ¨ul Varol

Reference 35

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Observation 0f57e5c2-ba43-4366-8b55-1c87d14526e0 · outbound

This paper cites Black, and G ¨ul Varol.

LS-GAN: Human Motion Synthesis with Latent-space GANs Black, and G ¨ul Varol

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.597326Z

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Observation 92d26bff-55a8-42d2-8f37-536f30cb20a1 · outbound

This paper cites Learning a bidirectional mapping between human whole- body motion and natural language using deep recurrent neu- ral networks.

LS-GAN: Human Motion Synthesis with Latent-space GANs Learning a bidirectional mapping between human whole- body motion and natural language using deep recurrent neu- ral networks

Reference 37

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Observation bef25f10-b804-416b-9d6f-b1111c494c9d · outbound

This paper cites Modi: Un- conditional motion synthesis from diverse data, 2022.

LS-GAN: Human Motion Synthesis with Latent-space GANs Modi: Un- conditional motion synthesis from diverse data, 2022

Reference 38

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Observation 3cb0f187-7733-4635-b379-4ea4605ff875 · outbound

This paper cites Learning transferable visual models from natural language supervision, 2021.

LS-GAN: Human Motion Synthesis with Latent-space GANs Learning transferable visual models from natural language supervision, 2021

Reference 39

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Observation 31d818bd-df93-4887-b5ba-59c958a3405b · outbound

This paper cites Learning transferable visual models from natural language supervision.

LS-GAN: Human Motion Synthesis with Latent-space GANs Learning transferable visual models from natural language supervision

Reference 40

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This paper cites High-resolution image syn- thesis with latent diffusion models, 2022.

LS-GAN: Human Motion Synthesis with Latent-space GANs High-resolution image syn- thesis with latent diffusion models, 2022

Reference 41

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This paper cites Improved techniques for training gans, 2016.

LS-GAN: Human Motion Synthesis with Latent-space GANs Improved techniques for training gans, 2016

Reference 42

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This paper cites Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis, 2023.

LS-GAN: Human Motion Synthesis with Latent-space GANs Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis, 2023

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.515210Z

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Observation 0ad9816d-b9e3-4dbb-9ede-3f1774633ee6 · outbound

This paper cites Adversarial diffusion distillation, 2023.

LS-GAN: Human Motion Synthesis with Latent-space GANs Adversarial diffusion distillation, 2023

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.498322Z

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Observation ad483e81-8a96-4e68-8c05-42a98ee20f6d · outbound

This paper cites Generative adversarial net- works (gans survey): Challenges, solutions, and future direc- tions, 2023.

LS-GAN: Human Motion Synthesis with Latent-space GANs Generative adversarial net- works (gans survey): Challenges, solutions, and future direc- tions, 2023

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.482816Z

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Observation 7eb3732b-f45f-4c4d-ae4c-d1efbb73d5d2 · outbound

This paper cites Human motion gen- eration using wasserstein gan.

LS-GAN: Human Motion Synthesis with Latent-space GANs Human motion gen- eration using wasserstein gan

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.467092Z

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Observation b4aef9e7-6fbf-4c75-a543-c8f83acd1d5a · outbound

This paper cites Bermano, and Daniel Cohen-Or.

LS-GAN: Human Motion Synthesis with Latent-space GANs Bermano, and Daniel Cohen-Or

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.451490Z

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Observation 1709d659-ef1c-4fa6-8dbd-f0ce73918b93 · outbound

This paper cites Human Motion Diffusion Model.

LS-GAN: Human Motion Synthesis with Latent-space GANs Human Motion Diffusion Model

Reference 49

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LS-GAN: Human Motion Synthesis with Latent-space GANs Unresolved cited work

Reference 50

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Observation cf6cccab-36fc-4e0a-94cb-473f31139086 · outbound

This paper cites Neural discrete representation learning,.

LS-GAN: Human Motion Synthesis with Latent-space GANs Neural discrete representation learning,

Reference 51

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Source-reported events for the cited work

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Observation 90140290-0bc8-4dc7-b2f7-8ab647248681 · outbound

This paper cites Actformer: A gan- based transformer towards general action-conditioned 3d hu- man motion generation, 2022.

LS-GAN: Human Motion Synthesis with Latent-space GANs Actformer: A gan- based transformer towards general action-conditioned 3d hu- man motion generation, 2022

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.412255Z

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Observation d1157c31-39a5-4316-b761-ccc8d85d8a10 · outbound

This paper cites Freeman, and Taesung Park.

LS-GAN: Human Motion Synthesis with Latent-space GANs Freeman, and Taesung Park

Reference 53

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This paper cites T2m-gpt: Generating human motion from textual de- scriptions with discrete representations, 2023.

LS-GAN: Human Motion Synthesis with Latent-space GANs T2m-gpt: Generating human motion from textual de- scriptions with discrete representations, 2023

Reference 54

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This paper cites MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model.

LS-GAN: Human Motion Synthesis with Latent-space GANs MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model

Reference 55

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This paper cites LS-GAN qualitative results on text-to-motion: a.A person is skipping rope.

LS-GAN: Human Motion Synthesis with Latent-space GANs LS-GAN qualitative results on text-to-motion: a.A person is skipping rope

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:16:11.369671Z

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Pith citing papers

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Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward cites this paper.

Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward LS-GAN: Human Motion Synthesis with Latent-space GANs

Reference 108

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