Paper Citation Record · LEDGER

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model

As of 11 August 2026, this Paper Citation Record lists 76 of 76 outbound references and 7 inbound Pith citation observations for arXiv:2412.14559.

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

pith.paper-citation-record.v1
2412.14559 v1

Coverage vector

measured 76 of 76 reference resolution

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measured 83 of 83 standing notices

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measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: pith, observed 2026-08-05T21:55:03.978993Z

Reference resolution

76 of 76 outbound references displayed

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External citation measurements

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Outbound references

Observation adb027cd-b392-41f3-aaea-f9b9caaccac3 · outbound

This paper cites an unresolved cited work.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Unresolved cited work

Reference 1

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Observation 6957c274-1944-42b9-9f2e-f8ff7790c82e · outbound

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

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Text2action: Generative adversarial synthesis from language to action

Reference 2

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Observation 812899fe-4156-406e-ae98-5842b42b5101 · outbound

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

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Lan- guage2pose: Natural language grounded pose forecasting

Reference 3

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Observation 475ff2b2-ba99-4480-b512-c7bc7ad4556e · outbound

This paper cites Teach: Temporal action composition for 3d hu- mans.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Teach: Temporal action composition for 3d hu- mans

Reference 4

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This paper cites Qwen Technical Report.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Qwen Technical Report

Reference 5

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Observation be5406ec-a403-4890-8efc-e99851361e7a · outbound

This paper cites Scaling to very very large corpora for natural language disambiguation.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Scaling to very very large corpora for natural language disambiguation

Reference 6

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Observation aa45d2de-c23f-4a78-8a98-936b78ea3fc4 · outbound

This paper cites Seamless human motion composition with blended posi- tional encodings.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Seamless human motion composition with blended posi- tional encodings

Reference 7

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Observation 0507e1bd-c9a7-4b5d-a77d-a8d8a8a789f4 · outbound

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

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Text2gestures: A transformer-based network for generating emotive body gestures for virtual agents

Reference 8

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This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 9

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Observation 651409a8-8db3-4d20-84eb-0a2306bece25 · outbound

This paper cites Video generation models as world simulators.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Video generation models as world simulators

Reference 10

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Observation 0455f183-131d-4ea5-a7ce-bea88016eb2f · outbound

This paper cites Language Models are Few-Shot Learners.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Language Models are Few-Shot Learners

Reference 11

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Observation 8d941bc6-d5bc-478c-9826-e0ec57caa777 · outbound

This paper cites Pay Attention and Move Better: Harnessing Attention for Interactive Motion Generation and Training-free Editing.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Pay Attention and Move Better: Harnessing Attention for Interactive Motion Generation and Training-free Editing

Reference 12

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This paper cites Executing your commands via mo- tion diffusion in latent space.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Executing your commands via mo- tion diffusion in latent space

Reference 13

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This paper cites Mofusion: A framework for denoising-diffusion-based motion synthesis.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Mofusion: A framework for denoising-diffusion-based motion synthesis

Reference 14

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Observation 8f1f662a-6d33-40fd-80b7-56d39881410d · outbound

This paper cites Motionlcm: Real-time control- lable motion generation via latent consistency model.ECCV,.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Motionlcm: Real-time control- lable motion generation via latent consistency model.ECCV,

Reference 15

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Observation c729bf44-528b-4da9-ba62-7f0ac1f8cad9 · outbound

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

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Ac- tion2motion: Conditioned generation of 3d human motions

Reference 16

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Observation 6fc82a58-b56b-4978-809a-2637375cfff9 · outbound

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

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Generating diverse and natural 3d human motions from text

Reference 17

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Observation bcaecc53-f22d-465d-b265-bd585058bdb2 · outbound

This paper cites Tm2t: Stochastic and tokenized modeling for the reciprocal gener- ation of 3d human motions and texts.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Tm2t: Stochastic and tokenized modeling for the reciprocal gener- ation of 3d human motions and texts

Reference 18

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This paper cites Momask: Generative masked mod- eling of 3d human motions.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Momask: Generative masked mod- eling of 3d human motions

Reference 19

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This paper cites Amd: Autoregressive motion diffusion.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Amd: Autoregressive motion diffusion

Reference 20

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Observation dde2a7c9-2e7a-4300-85ca-02da2e607ca6 · outbound

This paper cites Deep Learning Scaling is Predictable, Empirically.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Deep Learning Scaling is Predictable, Empirically

Reference 21

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This paper cites Be- yond human-level accuracy: Computational challenges in deep learning.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Be- yond human-level accuracy: Computational challenges in deep learning

Reference 22

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This paper cites Denoising diffu- sion probabilistic models.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Denoising diffu- sion probabilistic models

Reference 23

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This paper cites Training compute-optimal large language mod- els.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Training compute-optimal large language mod- els

Reference 24

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This paper cites Avatarclip: Zero-shot text- driven generation and animation of 3d avatars.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Avatarclip: Zero-shot text- driven generation and animation of 3d avatars

Reference 25

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This paper cites Stablemofusion: Towards robust and efficient diffusion-based motion generation framework.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Stablemofusion: Towards robust and efficient diffusion-based motion generation framework

Reference 26

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

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Motiongpt: Human motion as a foreign language

Reference 27

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This paper cites Scaling Laws for Neural Language Models.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Scaling Laws for Neural Language Models

Reference 28

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This paper cites Guided motion diffusion for controllable human motion synthesis.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Guided motion diffusion for controllable human motion synthesis

Reference 29

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This paper cites Omg: Towards open-vocabulary motion generation via mix- ture of controllers.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Omg: Towards open-vocabulary motion generation via mix- ture of controllers

Reference 30

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This paper cites Scaling laws for diffusion transformers.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Scaling laws for diffusion transformers

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ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Motion-x: A large-scale 3d expressive whole-body human motion dataset

Reference 32

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ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Human Motion Modeling using DVGANs

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This paper cites Plan, posture and go: Towards open-world text-to-motion generation.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Plan, posture and go: Towards open-world text-to-motion generation

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ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Humantomato: Text-aligned whole-body motion generation

Reference 35

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ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Perpetual humanoid control for real-time simulated avatars

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This paper cites Amass: Archive of mo- tion capture as surface shapes.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Amass: Archive of mo- tion capture as surface shapes

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This paper cites Finite Scalar Quantization: VQ-VAE Made Simple.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Finite Scalar Quantization: VQ-VAE Made Simple

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

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Temos: Generating diverse human motions from textual descriptions

Reference 40

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This paper cites Multi-track timeline control for text-driven 3d human motion generation.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Multi-track timeline control for text-driven 3d human motion generation

Reference 41

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This paper cites The kit motion-language dataset.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model The kit motion-language dataset

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

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Learning a bidirectional mapping between human whole- body motion and natural language using deep recurrent neu- ral networks

Reference 43

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This paper cites Learning transferable visual models from natural language supervi- sion.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Learning transferable visual models from natural language supervi- sion

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ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Hierarchical Text-Conditional Image Generation with CLIP Latents

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ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model High-resolution image synthesis with latent diffusion models

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ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Human motion diffusion as a generative prior

Reference 48

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This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Deep unsupervised learning using nonequilibrium thermodynamics

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ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Denois- ing diffusion implicit models

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ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

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This paper cites Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies

Reference 52

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Observation 7d74d863-dd77-4ad4-8462-fc3dda7d43c0 · outbound

This paper cites Motionclip: Exposing human motion generation to clip space.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Motionclip: Exposing human motion generation to clip space

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.647972Z

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Observation 3346b231-9a4d-429c-948b-1007480936d6 · outbound

This paper cites Human motion dif- fusion model.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Human motion dif- fusion model

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.635367Z

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Observation 34006e3b-8e57-4025-ba2d-af0562d34c6d · outbound

This paper cites Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

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Observation 8dfc7d97-725e-4fa1-b315-66f4abeb0945 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model LLaMA: Open and Efficient Foundation Language Models

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Observation 9d1c70ab-2c5f-4bc8-a3a7-6514ba178e8e · outbound

This paper cites Attention is all you need.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Attention is all you need

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.623595Z

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Observation e37a622f-b2e0-48db-89a3-25c1bedc87e3 · outbound

This paper cites Tlcontrol: Trajectory and language control for human motion synthesis.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Tlcontrol: Trajectory and language control for human motion synthesis

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.611471Z

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Observation 948a2843-422c-459b-9dac-beb76ede4a25 · outbound

This paper cites Scaling Large Motion Models with Million-Level Human Motions.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Scaling Large Motion Models with Million-Level Human Motions

Reference 59

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Observation 4ac4a342-1cfb-4aea-9b5f-5ba6281d16b1 · outbound

This paper cites Humanise: Language-conditioned hu- man motion generation in 3d scenes.NeurIPS, pages 14959– 14971, 2022.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Humanise: Language-conditioned hu- man motion generation in 3d scenes.NeurIPS, pages 14959– 14971, 2022

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.598617Z

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Observation 32580192-e64b-4cf8-ac2b-dce43644de1b · outbound

This paper cites Move as you say interact as you can: Language-guided human motion generation with scene af- fordance.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Move as you say interact as you can: Language-guided human motion generation with scene af- fordance

Reference 61

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Observation 407a146a-3316-470b-a054-cb64d5b360fc · outbound

This paper cites Motion-Agent: A Conversational Framework for Human Motion Generation with LLMs.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Motion-Agent: A Conversational Framework for Human Motion Generation with LLMs

Reference 62

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Observation 405fbf7e-0915-443c-974e-aa8e7174b102 · outbound

This paper cites Unified human-scene interaction via prompted chain-of-contacts.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Unified human-scene interaction via prompted chain-of-contacts

Reference 63

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Observation 6ca04489-2266-46e6-bb93-6436bee6b3f1 · outbound

This paper cites Omnicontrol: Control any joint at any time for human motion generation.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Omnicontrol: Control any joint at any time for human motion generation

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Observation 9aab5317-16fa-402f-adb1-3b20d3746fd5 · outbound

This paper cites Towards detailed text-to- motion synthesis via basic-to-advanced hierarchical diffu- sion model.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Towards detailed text-to- motion synthesis via basic-to-advanced hierarchical diffu- sion model

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.558624Z

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Observation 051829d3-87fc-4a51-a959-64eb0a9fffc4 · outbound

This paper cites Inter-x: Towards versatile human- human interaction analysis.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Inter-x: Towards versatile human- human interaction analysis

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.546555Z

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Observation cf1abbe4-999d-4754-aa7b-cc695edb37e0 · outbound

This paper cites Animationgpt:an aigc tool for gen- erating game combat motion assets.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Animationgpt:an aigc tool for gen- erating game combat motion assets

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.533943Z

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Observation 69a2cc14-8469-400b-ba21-b88b07f4fd1d · outbound

This paper cites Physdiff: Physics-guided human motion diffusion model.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Physdiff: Physics-guided human motion diffusion model

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.521543Z

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Observation 9b6903ca-7365-4df3-816d-fe5610e36679 · outbound

This paper cites Generating human motion from textual descriptions with discrete representations.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Generating human motion from textual descriptions with discrete representations

Reference 69

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Observation e8594542-ea48-4b7a-a94f-d6bd7c2486fc · outbound

This paper cites Gener- ative motion stylization of cross-structure characters within canonical motion space.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Gener- ative motion stylization of cross-structure characters within canonical motion space

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Observation b0a3dafd-5e19-43b6-9ee7-eec8a61523b4 · outbound

This paper cites Re- modiffuse: Retrieval-augmented motion diffusion model.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Re- modiffuse: Retrieval-augmented motion diffusion model

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.482337Z

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Observation 099309dc-31c7-45f7-b58e-305dfeaec6f0 · outbound

This paper cites Motiondif- fuse: Text-driven human motion generation with diffusion model.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Motiondif- fuse: Text-driven human motion generation with diffusion model

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.467432Z

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Observation 9010eb86-121b-4101-a49d-7cb803c00a23 · outbound

This paper cites Mo- tiongpt: Finetuned llms are general-purpose motion genera- tors.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Mo- tiongpt: Finetuned llms are general-purpose motion genera- tors

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.455343Z

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Observation fabe9f25-6de2-486b-8942-a76bd166013d · outbound

This paper cites Smoodi: Stylized motion diffusion model.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Smoodi: Stylized motion diffusion model

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.439056Z

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Observation 180f6461-1eb6-48fc-9c97-8eea69ddb622 · outbound

This paper cites Emdm: Efficient mo- tion diffusion model for fast, high-quality motion generation.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Emdm: Efficient mo- tion diffusion model for fast, high-quality motion generation

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.412857Z

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Observation ff6eb552-ea5a-4b72-a956-2c7967f4aeac · outbound

This paper cites ""Open AI method for forward pass FLOPs counting of decoder-only Transformer 3.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model ""Open AI method for forward pass FLOPs counting of decoder-only Transformer 3

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:13:12.388847Z

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Pith citing papers

Observation e0af119d-2182-4dee-b2f6-3e788655aca5 · inbound

Hunyuan-Game: Industrial-grade Intelligent Game Creation Model cites this paper.

Hunyuan-Game: Industrial-grade Intelligent Game Creation Model ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model

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Observation 6e159d06-52a7-4b2f-90b6-4268031d9aef · inbound

Absolute Coordinates Make Motion Generation Easy cites this paper.

Absolute Coordinates Make Motion Generation Easy ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model

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Observation 6086b100-aee4-499b-a512-71604a30094c · inbound

CoDA: Coordinated Diffusion Noise Optimization for Whole-Body Manipulation of Articulated Objects cites this paper.

CoDA: Coordinated Diffusion Noise Optimization for Whole-Body Manipulation of Articulated Objects ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model

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Observation be5f298d-d39a-4922-8829-783ea480857a · inbound

Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data cites this paper.

Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model

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Observation 4ae44264-f948-4cca-937d-02e8bf0a804b · inbound

Being-M0.5: A Real-Time Controllable Vision-Language-Motion Model cites this paper.

Being-M0.5: A Real-Time Controllable Vision-Language-Motion Model ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model

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Observation 4a388259-6b2e-4cc3-a545-33f1af27ddcf · inbound

OmniMotion-X: Versatile Multimodal Whole-Body Motion Generation cites this paper.

OmniMotion-X: Versatile Multimodal Whole-Body Motion Generation ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model

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Observation 2b0ec709-cd13-4007-ae40-5d5d415739aa · inbound

MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation cites this paper.

MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model

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