Grounding Intelligence in Movement | Paper Citation Record

Observation 651631b1-8bd2-417a-a1ab-e0ec7b864567 · outbound

This paper cites GPT-4 Technical Report.

Grounding Intelligence in Movement GPT-4 Technical Report

Reference 1

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Observation cbea5d6c-2af4-48c4-a9e3-0f92c51cfc1f · outbound

This paper cites Cosmos World Foundation Model Platform for Physical AI.

Grounding Intelligence in Movement Cosmos World Foundation Model Platform for Physical AI

Reference 2

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Observation ba0fe70c-df44-4f50-8ce8-addf6dcf12e5 · outbound

This paper cites Curriculum Reinforcement Learning via Morphology-Environment Co-Evolution.

Grounding Intelligence in Movement Curriculum Reinforcement Learning via Morphology-Environment Co-Evolution

Reference 3

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Observation 2ac69df4-763e-42f4-99cc-ba919fd6a3d1 · outbound

This paper cites MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.

Grounding Intelligence in Movement MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis

Reference 4

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This paper cites A unified, scalable framework for neural population decoding.

Grounding Intelligence in Movement A unified, scalable framework for neural population decoding

Reference 5

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Observation 9ea0d2fb-c8a0-490a-8136-cf40a0b843a1 · outbound

This paper cites Relax, it doesn’t matter how you get there: A new self-supervised ap- proach for multi-timescale behavior analysis.

Grounding Intelligence in Movement Relax, it doesn’t matter how you get there: A new self-supervised ap- proach for multi-timescale behavior analysis

Reference 6

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This paper cites 3D bird reconstruction: a dataset, model, and shape recovery from a single view.

Grounding Intelligence in Movement 3D bird reconstruction: a dataset, model, and shape recovery from a single view

Reference 7

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Observation 89a7f6fb-2c69-46b8-8a9f-1164cbb94ab4 · outbound

This paper cites ChatGarment: Garment Estimation, Generation and Editing via Large Language Models.

Grounding Intelligence in Movement ChatGarment: Garment Estimation, Generation and Editing via Large Language Models

Reference 8

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Observation 26879e42-7df6-4ae1-9d38-f7f01e9ba3d8 · outbound

This paper cites OmniJet-α: the first cross-task foundation model for particle physics.

Grounding Intelligence in Movement OmniJet-α: the first cross-task foundation model for particle physics

Reference 9

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Observation dde691e6-04e0-455f-aa5b-e891b6ef2eba · outbound

This paper cites Video generation models as world simulators.

Grounding Intelligence in Movement Video generation models as world simulators

Reference 10

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Observation 405235f8-a968-4695-9842-0bc523ad48b3 · outbound

This paper cites MyoSuite -- A contact-rich simulation suite for musculoskeletal motor control.

Grounding Intelligence in Movement MyoSuite -- A contact-rich simulation suite for musculoskeletal motor control

Reference 11

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Observation 75a38b37-a2eb-4b59-968f-6246b3b4bdfa · outbound

This paper cites Smpler-x: Scaling up expressive human pose and shape estimation.

Grounding Intelligence in Movement Smpler-x: Scaling up expressive human pose and shape estimation

Reference 12

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Observation d51ebeb2-27ff-4ce1-9a8d-4e3fec385dbb · outbound

This paper cites A Short Note on the Kinetics-700 Human Action Dataset.

Grounding Intelligence in Movement A Short Note on the Kinetics-700 Human Action Dataset

Reference 13

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Observation b6eb3533-cfbd-4edc-804c-aa73aa950da5 · outbound

This paper cites CAPTURE-24: A large dataset of wrist-worn activity tracker data collected in the wild for human activity recognition.

Grounding Intelligence in Movement CAPTURE-24: A large dataset of wrist-worn activity tracker data collected in the wild for human activity recognition

Reference 14

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Observation 71ba3e78-a4cb-4fd4-b8b0-7390129207a9 · outbound

This paper cites Mammalnet: A large-scale video benchmark for mammal recognition and behavior understanding.

Grounding Intelligence in Movement Mammalnet: A large-scale video benchmark for mammal recognition and behavior understanding

Reference 15

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Observation c46a81ec-02b1-4ec5-ab43-cb66102d8b74 · outbound

This paper cites Enhancing Vision Foundation Models via Multimodal Continual Pre-Training.

Grounding Intelligence in Movement Enhancing Vision Foundation Models via Multimodal Continual Pre-Training

Reference 16

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Observation a2ffbd3c-66f5-4b41-b4c4-de67c68267b0 · outbound

This paper cites Bio-Inspired Motion Emulation for Social Robots: A Real-Time Trajectory Generation and Control Approach.

Grounding Intelligence in Movement Bio-Inspired Motion Emulation for Social Robots: A Real-Time Trajectory Generation and Control Approach

Reference 17

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Observation 5a5ab891-a87b-4e46-9dc3-8ad5398573d9 · outbound

This paper cites Muscles in action.

Grounding Intelligence in Movement Muscles in action

Reference 18

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Observation 7b376c8d-4842-4f14-9db9-5e881a966a49 · outbound

This paper cites The Devonian tetrapod Acanthostega gunnari Jarvik: postcranial anatomy, basal tetrapod interrelationships and patterns of skeletal evolution.

Grounding Intelligence in Movement The Devonian tetrapod Acanthostega gunnari Jarvik: postcranial anatomy, basal tetrapod interrelationships and patterns of skeletal evolution

Reference 19

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Observation 43eb5843-1de9-4197-b4e1-f26a75b62dce · outbound

This paper cites Openmmlab 3d human parametric model toolbox and bench- mark.

Grounding Intelligence in Movement Openmmlab 3d human parametric model toolbox and bench- mark

Reference 20

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Observation 76f619f3-79f9-40ab-82e2-b465edb92240 · outbound

This paper cites Neuro-gpt: Towards a foundation model for eeg.

Grounding Intelligence in Movement Neuro-gpt: Towards a foundation model for eeg

Reference 21

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Observation 07c21a6b-6f0c-473f-8d1f-b85175a1a71f · outbound

This paper cites OpenSim: open-source software to create and analyze dynamic sim- ulations of movement.

Grounding Intelligence in Movement OpenSim: open-source software to create and analyze dynamic sim- ulations of movement

Reference 22

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Observation 2efd5d14-3d46-4f40-8c00-c75804bd31af · outbound

This paper cites A review of 3D human pose estimation algorithms for markerless motion capture.

Grounding Intelligence in Movement A review of 3D human pose estimation algorithms for markerless motion capture

Reference 23

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Observation ac1bc908-c2bd-465b-9ca3-ac09a90736db · outbound

This paper cites Muscles of vertebrates: comparative anatomy, evolution, homologies and development.

Grounding Intelligence in Movement Muscles of vertebrates: comparative anatomy, evolution, homologies and development

Reference 24

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Observation fa915dd4-129e-472c-a01e-514db1aa7141 · outbound

This paper cites WANDR: Intention-guided human motion generation.

Grounding Intelligence in Movement WANDR: Intention-guided human motion generation

Reference 25

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Observation 1b5f295d-0e88-400b-9374-0d3ac290047d · outbound

This paper cites Project Aria: A New Tool for Egocentric Multi-Modal AI Research.

Grounding Intelligence in Movement Project Aria: A New Tool for Egocentric Multi-Modal AI Research

Reference 26

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Observation 47f85ab7-4757-44bb-ad7c-73c32d4e7772 · outbound

This paper cites Chatpose: Chatting about 3d human pose.

Grounding Intelligence in Movement Chatpose: Chatting about 3d human pose

Reference 27

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Observation 0abc0506-3dc3-4d61-b5e8-1a0a564589f4 · outbound

This paper cites MoVi: A large multi-purpose human motion and video dataset.

Grounding Intelligence in Movement MoVi: A large multi-purpose human motion and video dataset

Reference 28

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Observation f199b213-0bc8-477d-987f-99290d3b8108 · outbound

This paper cites Imagebind: One embedding space to bind them all.

Grounding Intelligence in Movement Imagebind: One embedding space to bind them all

Reference 29

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Observation b8cf1974-f6b9-458a-990f-da6e2d295c59 · outbound

This paper cites MOMENT: A Family of Open Time-series Foundation Models.

Grounding Intelligence in Movement MOMENT: A Family of Open Time-series Foundation Models

Reference 30

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Observation 599f3b5e-c594-4a9e-a3a5-f6b9d49ccc1e · outbound

This paper cites On Memorization in Diffusion Models.

Grounding Intelligence in Movement On Memorization in Diffusion Models

Reference 31

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Observation 619e531d-75d3-49df-9880-425630d9c002 · outbound

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

Grounding Intelligence in Movement Generating diverse and natural 3d human motions from text

Reference 32

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Observation d2628929-443c-4c7f-bd19-a3aa4492be36 · outbound

This paper cites World Models.

Grounding Intelligence in Movement World Models

Reference 33

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Observation 7f2e36e2-5db1-41fe-bdd5-f13686ae5ddf · outbound

This paper cites Mastering Diverse Domains through World Models.

Grounding Intelligence in Movement Mastering Diverse Domains through World Models

Reference 34

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Observation c2c350db-7533-48fa-834b-c96d4b643673 · outbound

This paper cites Motion Diffusion Model for Long Motion Generation.

Grounding Intelligence in Movement Motion Diffusion Model for Long Motion Generation

Reference 35

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Observation 9c01a878-c8f9-487a-9d32-b721fa8b26a7 · outbound

This paper cites Denoising diffusion probabilistic models.

Grounding Intelligence in Movement Denoising diffusion probabilistic models

Reference 36

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Observation f189cc27-dac2-43f7-916b-62d1a83c384e · outbound

This paper cites Human3. 6m: Large scale datasets and predictive methods for 3d human sensing in natural environments.

Grounding Intelligence in Movement Human3. 6m: Large scale datasets and predictive methods for 3d human sensing in natural environments

Reference 37

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Observation de00bef2-fa93-436e-a9ae-25db5c516b92 · outbound

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

Grounding Intelligence in Movement Motiongpt: Human motion as a foreign language

Reference 38

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Observation 8d4970c7-865e-4927-a78e-77663e069369 · outbound

This paper cites Open access dataset and toolbox of high-density surface electromyogram recordings.

Grounding Intelligence in Movement Open access dataset and toolbox of high-density surface electromyogram recordings

Reference 39

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Observation a9017e99-3914-4916-8635-e2628426eeb1 · outbound

This paper cites Deep transfer learning in sheep activity recognition using ac- celerometer data.

Grounding Intelligence in Movement Deep transfer learning in sheep activity recognition using ac- celerometer data

Reference 40

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Observation 60ed8e6c-bc9f-466e-8b26-708d979b5a86 · outbound

This paper cites BioPose: Biomechanically-accurate 3D Pose Estimation from Monocular Videos.

Grounding Intelligence in Movement BioPose: Biomechanically-accurate 3D Pose Estimation from Monocular Videos

Reference 41

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Observation fc264688-7bb7-4db8-ba83-40ad48fd149e · outbound

This paper cites World Model-based Perception for Visual Legged Locomotion.

Grounding Intelligence in Movement World Model-based Perception for Visual Legged Locomotion

Reference 42

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Observation 137c8972-e828-4541-b7e4-dc7e04fd7c31 · outbound

This paper cites Foundation models for time series analysis: A tutorial and survey.

Grounding Intelligence in Movement Foundation models for time series analysis: A tutorial and survey

Reference 43

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Observation bf7e1aca-ea6a-4fd1-bc3e-741f30eeb715 · outbound

This paper cites Video-LLaVA: Learning United Visual Representation by Alignment Before Projection.

Grounding Intelligence in Movement Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 44

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Observation c4e73ec7-cc9c-4db0-9ba8-9294383e47ce · outbound

This paper cites Motion-x: A large-scale 3d expressive whole-body human motion dataset.

Grounding Intelligence in Movement Motion-x: A large-scale 3d expressive whole-body human motion dataset

Reference 45

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This paper cites Graph Foundation Models: Concepts, Opportunities and Challenges.

Grounding Intelligence in Movement Graph Foundation Models: Concepts, Opportunities and Challenges

Reference 46

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This paper cites Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks.

Grounding Intelligence in Movement Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks

Reference 47

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Observation 922f94fa-dc42-41a0-82e8-b6c13c2579e4 · outbound

This paper cites HUMOTO: A 4D Dataset of Mocap Human Object Interactions.

Grounding Intelligence in Movement HUMOTO: A 4D Dataset of Mocap Human Object Interactions

Reference 48

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Observation a4e71653-e0e3-4916-be2d-9bb204a58c1d · outbound

This paper cites M$^3$GPT: An Advanced Multimodal, Multitask Framework for Motion Comprehension and Generation.

Grounding Intelligence in Movement M$^3$GPT: An Advanced Multimodal, Multitask Framework for Motion Comprehension and Generation

Reference 49

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Observation b77630b0-65c8-45d4-89e3-9df96bb7f0d8 · outbound

This paper cites Nymeria: A massive collection of multimodal egocentric daily motion in the wild.

Grounding Intelligence in Movement Nymeria: A massive collection of multimodal egocentric daily motion in the wild

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:38.794798Z

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Observation c3d6139e-0d3e-4f66-a14a-abece899a2ce · outbound

This paper cites Chimpact: A longitudinal dataset for understanding chimpanzee be- haviors.

Grounding Intelligence in Movement Chimpact: A longitudinal dataset for understanding chimpanzee be- haviors

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:38.698669Z

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Observation 7d6e3d0b-66a6-4753-ba97-a7f680cc9eaf · outbound

This paper cites AMASS: Archive of motion capture as surface shapes.

Grounding Intelligence in Movement AMASS: Archive of motion capture as surface shapes

Reference 52

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Observation a1f440a3-d48e-4014-85d9-3a1ef9a6b8c0 · outbound

This paper cites FedAAR: A novel federated learning framework for animal activity recogni- tion with wearable sensors.

Grounding Intelligence in Movement FedAAR: A novel federated learning framework for animal activity recogni- tion with wearable sensors

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:38.542039Z

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Observation 87a8b7e4-6853-4654-946f-70ef535521ab · outbound

This paper cites DeepLabCut: markerless pose estimation of user-defined body parts with deep learning.

Grounding Intelligence in Movement DeepLabCut: markerless pose estimation of user-defined body parts with deep learning

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:38.487213Z

Source-reported events for the cited work

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Observation 1fa3765c-95e5-443e-8450-66dd84a2da80 · outbound

This paper cites Deep learning, reinforcement learning, and world models.

Grounding Intelligence in Movement Deep learning, reinforcement learning, and world models

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:38.353561Z

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Observation 61313c8e-db6e-453f-aa26-17469ac6f6aa · outbound

This paper cites Act-ChatGPT: Introducing Action Features into Multi- modal Large Language Models for Video Understanding.

Grounding Intelligence in Movement Act-ChatGPT: Introducing Action Features into Multi- modal Large Language Models for Video Understanding

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:38.261834Z

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Observation 58b134d6-fd30-411f-9e43-489566660959 · outbound

This paper cites Combining Model-based and Data-based approaches for online predic- tions of human trajectories.

Grounding Intelligence in Movement Combining Model-based and Data-based approaches for online predic- tions of human trajectories

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:38.199445Z

Source-reported events for the cited work

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Observation 85eb7ac8-d8eb-4722-bdf1-1777208ddc1a · outbound

This paper cites Exploring deep learning techniques for wild animal behaviour clas- sification using animal-borne accelerometers.

Grounding Intelligence in Movement Exploring deep learning techniques for wild animal behaviour clas- sification using animal-borne accelerometers

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:38.090141Z

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This paper cites Real-time EMG based pattern recognition control for hand prosthe- ses: A review on existing methods, challenges and future implementation.

Grounding Intelligence in Movement Real-time EMG based pattern recognition control for hand prosthe- ses: A review on existing methods, challenges and future implementation

Reference 59

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Observation e7042a06-c775-42c7-87c8-e345373ba149 · outbound

This paper cites Genie 2: A large-scale foundation world model.

Grounding Intelligence in Movement Genie 2: A large-scale foundation world model

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:37.866800Z

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Observation a9d4b9ed-6faf-4f52-832f-eabec6d84d95 · outbound

This paper cites SLEAP: A deep learning system for multi-animal pose tracking.

Grounding Intelligence in Movement SLEAP: A deep learning system for multi-animal pose tracking

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:37.777233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cdcc9dd7-ea66-4800-85e8-8c43c913cf6c · outbound

This paper cites Generating meaning: active inference and the scope and limits of passive AI.

Grounding Intelligence in Movement Generating meaning: active inference and the scope and limits of passive AI

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:37.695290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation caa09ac1-1f48-404e-811a-583d5f93ff74 · outbound

This paper cites Wearable sensor-based real-time gait detection: A systematic review.

Grounding Intelligence in Movement Wearable sensor-based real-time gait detection: A systematic review

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:37.586688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c61cb92a-8752-4fe7-9346-d7e74a288b9c · outbound

This paper cites A generic noninvasive neuromotor interface for human- computer interaction.

Grounding Intelligence in Movement A generic noninvasive neuromotor interface for human- computer interaction

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:37.465060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 531d874c-24b5-4706-a242-765cd491cdbe · outbound

This paper cites A Generalist Agent.

Grounding Intelligence in Movement A Generalist Agent

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:29.212277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d60ff4e8-a49d-4123-9f26-e8efc0330867 · outbound

This paper cites Do robots outperform humans in human-centered domains?.

Grounding Intelligence in Movement Do robots outperform humans in human-centered domains?

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:37.375187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 09e97145-5b85-4f45-abe0-a8fa5b99f148 · outbound

This paper cites Embodied Hands: Modeling and Capturing Hands and Bodies Together.

Grounding Intelligence in Movement Embodied Hands: Modeling and Capturing Hands and Bodies Together

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:29.388145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55d26830-91d9-4959-99ad-f6b92193c9ab · outbound

This paper cites DiffLocks: Generating 3D Hair from a Single Image using Diffusion Models.

Grounding Intelligence in Movement DiffLocks: Generating 3D Hair from a Single Image using Diffusion Models

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-08-06T20:25:33.620967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 958170bd-4fa7-4fc7-97cc-7d835b69b89d · outbound

This paper cites AudioPaLM: A Large Language Model That Can Speak and Listen.

Grounding Intelligence in Movement AudioPaLM: A Large Language Model That Can Speak and Listen

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:29.530529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b9a590a-3f2d-4e3c-8db8-2eed04cd5389 · outbound

This paper cites Human motion trajectory prediction: A survey.

Grounding Intelligence in Movement Human motion trajectory prediction: A survey

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:37.274106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f8d535ac-68cd-46e0-88fb-0499f1ea3c1e · outbound

This paper cites emg2pose: A large and diverse benchmark for surface electromyographic hand pose estimation.

Grounding Intelligence in Movement emg2pose: A large and diverse benchmark for surface electromyographic hand pose estimation

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:37.188240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 27503b08-f806-45ac-9421-ceee70884ed6 · outbound

This paper cites DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems.

Grounding Intelligence in Movement DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:29.745329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8404669b-562d-4229-aa0d-fb9747ef4bd2 · outbound

This paper cites Movement science needs different pose tracking algorithms.

Grounding Intelligence in Movement Movement science needs different pose tracking algorithms

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-08-06T20:25:33.476194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f9f7a929-b2fc-4c82-b339-5a1074450c2c · outbound

This paper cites Reinforcement learning- based motion imitation for physiologically plausible musculoskeletal motor control.

Grounding Intelligence in Movement Reinforcement learning- based motion imitation for physiologically plausible musculoskeletal motor control

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:29.865938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cfe54d3-99c5-434e-a145-f63d691b3f19 · outbound

This paper cites Riemanngfm: Learning a graph foundation model from riemannian geometry.

Grounding Intelligence in Movement Riemanngfm: Learning a graph foundation model from riemannian geometry

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:37.052245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2a67182b-1ba8-4c4f-9035-b59b1ad7b5aa · outbound

This paper cites Diffposetalk: Speech-driven stylistic 3d facial animation and head pose generation via diffusion models.

Grounding Intelligence in Movement Diffposetalk: Speech-driven stylistic 3d facial animation and head pose generation via diffusion models

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:36.953137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 24d0a924-7dc2-4a02-a0a5-e76a28aeba9b · outbound

This paper cites TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis.

Grounding Intelligence in Movement TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:30.269114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc0bd1bd-1600-47c8-9f70-e20509ff6973 · outbound

This paper cites GaitDynamics: A Generative Foundation Model for Analyzing Human Walking and Running.

Grounding Intelligence in Movement GaitDynamics: A Generative Foundation Model for Analyzing Human Walking and Running

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:36.844605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9f5ead57-bb1f-4052-a7e2-d5fe01dc6b6d · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Grounding Intelligence in Movement Gemini: A Family of Highly Capable Multimodal Models

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:30.515509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c5a148d-74f1-407e-888a-51f3367bfaa6 · outbound

This paper cites Human Motion Diffusion Model.

Grounding Intelligence in Movement Human Motion Diffusion Model

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:30.631187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 458b8e64-fc66-4c12-9677-b18d87d828df · outbound

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

Grounding Intelligence in Movement Mujoco: A physics engine for model-based control

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:36.742195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4142ab88-7d68-436c-a1fe-8379ca7237d7 · outbound

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

Grounding Intelligence in Movement LLaMA: Open and Efficient Foundation Language Models

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:30.904731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08759310-c3dc-4ffc-b3ee-d865124aadb3 · outbound

This paper cites MammAlps: A multi-view video behavior monitoring dataset of wild mam- mals in the Swiss Alps.

Grounding Intelligence in Movement MammAlps: A multi-view video behavior monitoring dataset of wild mam- mals in the Swiss Alps

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:36.579221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e4febe30-d638-4339-abaa-9a7fc50d5b2b · outbound

This paper cites Evaluating the world model implicit in a generative model.

Grounding Intelligence in Movement Evaluating the world model implicit in a generative model

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:36.454640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fb386193-1b11-45ad-91fa-259518efbeb8 · outbound

This paper cites MmCows: A Multimodal Dataset for Dairy Cattle Monitoring.

Grounding Intelligence in Movement MmCows: A Multimodal Dataset for Dairy Cattle Monitoring

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:36.341436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 93ac2619-56de-404f-8831-3a421686e92f · outbound

This paper cites Videomae v2: Scaling video masked autoencoders with dual masking.

Grounding Intelligence in Movement Videomae v2: Scaling video masked autoencoders with dual masking

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:31.527216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca50f6e2-20ba-4f63-9586-8cba6d1cd145 · outbound

This paper cites PromptHMR: Promptable Human Mesh Recovery.

Grounding Intelligence in Movement PromptHMR: Promptable Human Mesh Recovery

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:31.588608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4df643a0-95f3-4bba-8055-c8a0408cdf28 · outbound

This paper cites OmniBind: Large-scale Omni Multimodal Representation via Binding Spaces.

Grounding Intelligence in Movement OmniBind: Large-scale Omni Multimodal Representation via Binding Spaces

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:31.654242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eebd6494-afd8-484f-bc39-13f2256175ce · outbound

This paper cites The application of wearable sensors and machine learning algorithms in rehabilitation training: A systematic review.

Grounding Intelligence in Movement The application of wearable sensors and machine learning algorithms in rehabilitation training: A systematic review

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:36.167340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ad68d4dd-36c7-4e52-8cbd-779f9d7e5df0 · outbound

This paper cites Addbiomechanics dataset: Capturing the physics of human motion at scale.

Grounding Intelligence in Movement Addbiomechanics dataset: Capturing the physics of human motion at scale

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:36.004450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9561229a-6aa1-41ef-80e5-b3f1e43f953c · outbound

This paper cites ivideogpt: Interactive videogpts are scalable world models.

Grounding Intelligence in Movement ivideogpt: Interactive videogpts are scalable world models

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:35.869544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6faf0b44-0cdc-4978-9657-08dde87293a6 · outbound

This paper cites Anygraph: Graph foundation model in the wild.

Grounding Intelligence in Movement Anygraph: Graph foundation model in the wild

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:35.752439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 61c44d8f-2c03-4537-81f3-f05ff083eff8 · outbound

This paper cites Robot learning in the era of foundation models: A survey.

Grounding Intelligence in Movement Robot learning in the era of foundation models: A survey

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:35.604349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 31fda091-a2f5-4db1-8a82-5b405bc0ef10 · outbound

This paper cites Vitpose: Simple vision transformer baselines for human pose estimation.

Grounding Intelligence in Movement Vitpose: Simple vision transformer baselines for human pose estimation

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:35.417701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0194a3b3-0901-4af8-9e0b-92ac7bcf0811 · outbound

This paper cites Vitpose++: Vision transformer for generic body pose estimation.

Grounding Intelligence in Movement Vitpose++: Vision transformer for generic body pose estimation

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:35.280575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2d3af8f3-98af-4340-877c-03594e981718 · outbound

This paper cites LLaV Action: evaluating and training multi-modal large language models for action recognition.

Grounding Intelligence in Movement LLaV Action: evaluating and training multi-modal large language models for action recognition

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:32.219198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2f4db6c-cdb1-4dd2-90e0-4d9363e6e895 · outbound

This paper cites SuperAnimal pretrained pose estimation models for behavioral analysis.

Grounding Intelligence in Movement SuperAnimal pretrained pose estimation models for behavioral analysis

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:35.139059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 52f8efa2-8ce2-4ba2-b1c7-65e567990673 · outbound

This paper cites Natural Language Can Help Bridge the Sim2Real Gap.

Grounding Intelligence in Movement Natural Language Can Help Bridge the Sim2Real Gap

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-06T20:25:32.433485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85905905-8bf1-4390-84ee-ab1bd77ce49a · outbound

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

Grounding Intelligence in Movement Physdiff: Physics-guided human motion diffusion model

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:34.986508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 22f5d15f-bb23-4c99-84f4-49a6feb8d133 · outbound

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

Grounding Intelligence in Movement Motiondiffuse: Text-driven human motion generation with diffusion model

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:25:34.819604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers