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Paper Citation Record · LEDGER

Grounding Intelligence in Movement

As of 10 August 2026, this Paper Citation Record lists 100 of 106 outbound references and 1 inbound Pith citation observation for arXiv:2507.02771.

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

pith.paper-citation-record.v1
2507.02771 v1

Coverage vector

measured 100 of 106 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:25:32.562488Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T12:56:32.421877Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T13:00:24.720063Z

Reference resolution

100 of 106 outbound references displayed

  • verified exact4
  • verified fuzzy39
  • unresolved57
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

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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source=pdf_text observed=2026-08-06T20:25:23.659772Z digest=sha256:907303da799ac01dee9b82e94a04d52a18d82d63ae34de8739e5249fe70ee55d

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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source=pdf_text observed=2026-08-06T20:25:23.799348Z digest=sha256:d0732d2a1c33ef577c4440265332108e678e48734aeef57991b5297320f6e9f4

Observation f28206bb-e014-4ede-8157-61629d06f205 · outbound

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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source=pdf_text observed=2026-08-06T20:25:23.884249Z digest=sha256:16d3dade6e46c169341c651c2bb3e679a597b4037223060bf4b3a8a4209be928

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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source=pdf_text observed=2026-08-06T20:25:23.953239Z digest=sha256:5d2aa31853bd99528b2c6fd857d00ca4876e0c58f52a4ff24c8d350845e64cda

Observation 1fef15f9-1773-4a52-9440-affb132d93fe · outbound

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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source=pdf_text observed=2026-08-06T20:25:24.034375Z digest=sha256:1464b29485d6c0c51ed23b9a9fde3fcfa52ac91742dba163bb64b21d847079cb

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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source=pdf_text observed=2026-08-06T20:25:24.120208Z digest=sha256:28e8ab9b94315429ae3c008b0d06f514eaebf55beef542eae44661bc916de8c3

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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source=pdf_text observed=2026-08-06T20:25:24.206030Z digest=sha256:56dd323668f6641ec1562b23b1df7cfcaa7ea1bab453ba3e1d4c16a9f23e6af4

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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source=pdf_text observed=2026-08-06T20:25:24.266076Z digest=sha256:a67be6b7fafddd29ad512950b93f6cd05e375d69b909e7487a87168f6bd641be

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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source=pdf_text observed=2026-08-06T20:25:24.356011Z digest=sha256:5d3bf15dd61e5a33e605452715e84dfc321701c801f67f402f8a7d0b313d80d9

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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source=pdf_text observed=2026-08-06T20:25:24.446668Z digest=sha256:5f4e8c87b0cb7311a7b7a941852add4df5ca298320af802795d28e0759daec04

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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source=pdf_text observed=2026-08-06T20:25:24.535632Z digest=sha256:1e262d33adc7bb0390500f54cb44f90cfff31c76abe0b3388008056cf142ad3f

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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source=pdf_text observed=2026-08-06T20:25:24.623742Z digest=sha256:9cc5fa5d645b5232fcf0701ba515649fbba8df8e5c07b71379004fa8f5f75eb0

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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source=pdf_text observed=2026-08-06T20:25:24.712629Z digest=sha256:16a0030ff60e7500e54fb84238a02a051b8933c79b2e2b20011ed85c968a531a

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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source=pdf_text observed=2026-08-06T20:25:24.829220Z digest=sha256:e8c3bcc52fd5478426dde0e30dad6c90cc5612d5cc8f2dcb1cb751fd3abba72e

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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source=pdf_text observed=2026-08-06T20:25:25.617444Z digest=sha256:3a7eafcb4f432427bccbe1549e7d08c3d6ac30628f80b5220ef9d5996fc994b4

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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source=pdf_text observed=2026-08-06T20:25:25.860646Z digest=sha256:fe0d44371c4bf122a8226c5b5ce474a2d0c489a637ecf2f1f8b2b4f3f1d6c541

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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source=pdf_text observed=2026-08-06T20:25:26.269422Z digest=sha256:41959f35977020b2469c1b9d85844c59ee1561916a7ef64f4aee23b207c460d9

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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source=pdf_text observed=2026-08-06T20:25:26.433785Z digest=sha256:b796f3446df9ac5b8f277923d3e806c32f7f5d96e7784874d594a700ad2fb081

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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source=pdf_text observed=2026-08-06T20:25:26.583706Z digest=sha256:a5e2a09267acd33c77c78726d6dc1d057654b95aee2d98b1568eef7e278a7f2d

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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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:26.852692Z digest=sha256:44d515fbd733427e31a9d0d4f08dcfb6eceecd4051f58e175c55d68d20eeffb3

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:39.136559Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:26.899146Z digest=sha256:18f48f9490f0e7ff1d4bc3bfaa39d4bcfdbb9b6676038bd8c18d2bfec512f5cf

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:26.970104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:26.970104Z digest=sha256:53c322c37ef8e31b23597e875d0b6542fd649909b762f0f24da5a85ec12f49ad

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

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:25:33.930249Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:27.086623Z digest=sha256:c5bd5af3dbee0c0bc879b66f7f3436e256b1eb6e7c29e5ce6c36516bd573b663

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:39.052494Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:27.267090Z digest=sha256:2e46e306b3b4e566922cce6b100175b39864c66d26de227da044d2d2a6b3f4d0

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:27.408179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:27.408179Z digest=sha256:6323dd4b1ce28826d88f0f43363547b7ec37ccc6d4ab9dc05d50666609e9da62

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:38.880201Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:27.446173Z digest=sha256:702994e505fc3ce0e386f57f8a5557b4ab6c394b735cb05ced1a5d70bf915641

Observation 4b439068-00a7-408b-8e40-13829c15735d · outbound

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

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

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:27.533051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:27.533051Z digest=sha256:e3deca0f84cdf4fab88596b167393ca0954ee4661c735b33aa290cca6981d7be

Observation e546804f-2ced-4318-aeb4-ad53f3e54008 · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:27.623864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:27.623864Z digest=sha256:11fa82e6a756975262c790ad2c251463e412cb42fc610ba88b9888084c709f25

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:27.774386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:27.774386Z digest=sha256:f328870380113e746d9e22d92ab06455954c5b0ecb905db30d30f79ad0736eec

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:27.903811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:27.903811Z digest=sha256:ae0ddade4911f791c1e8bd0823780e02849ffde28a0c6e59b595c5ca18941ed0

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:28.032363Z digest=sha256:76457625a6414585a4e502745a83aad3fbfb3b43e3a29ca116ca1f9fcce408b8

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:28.197627Z digest=sha256:47a2cece85dbf2dcd5670c2c86db240cf91cec3a401544ea9a7892b6dc1ad487

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:38.618720Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:28.282266Z digest=sha256:f20e35e29d63977180449400a23323e72c81e7f7077ed4d8e333024da3bca4fc

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:28.341149Z digest=sha256:7946215eb745447f5a10f0da74e72b8a2bfbbf9b044922e3820c4c77b6805351

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

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

source=pdf_text observed=2026-08-06T20:25:28.414973Z digest=sha256:7383601fbbd9b039b91641e195e8864fc9390ef144585c9d37d54565310a4178

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:28.526245Z digest=sha256:ecded2056c72a09e5011400429f6331408c7dc72388beba5a3cb30b048c82419

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:28.608515Z digest=sha256:f2fd3f4fb04b1af36d6fcb27506eaaa0d1037a19cc253bc7edb7098e4e3ca8d0

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

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

source=pdf_text observed=2026-08-06T20:25:28.647464Z digest=sha256:f8bfd721e21d46b4bf1151eecb605c5abb94f0bfadd4e2cd92963474b9846d9e

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:28.728964Z digest=sha256:4153dbf53983e3678a7aa6abfb3ac4f6dd0059b15846af6120189ac5d6f7b7a5

Observation a87b326a-a330-47da-bab6-4c1bcbe43b0a · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:37.969446Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:28.790201Z digest=sha256:8733a8bdc1e1c888c0c08c81e28a4eda093f0d58f3373fa7e09f31776a789d2e

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

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T20:25:28.847132Z digest=sha256:b47ffc5f232eae12ec989b265253313244e044343019643ffa50ea8c74f6f3d2

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:28.945744Z digest=sha256:62b17d4453bbf32d2dd40d97772f7e888cd53c19fce66e2c0ca7161834c333f1

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:28.991981Z digest=sha256:581d2652bfac2fcd7d46344e83e517c138ee1296d43fb78747d7ffa9fdfdea75

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:29.057250Z digest=sha256:98796b671fcaecd568ca27f61faf4b4e597b962ab76653bb5acff64c874c87bf

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:29.127125Z digest=sha256:456fce2a0db235761504b5b715a90a60abaca9826110ae4af3614d03a0381e8a

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.

source=pdf_text observed=2026-08-06T20:25:29.212277Z digest=sha256:2f7ad77e59ff19066f04f258f401915d46e3981b1c4d9d26771982578b3cdc81

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:29.301788Z digest=sha256:ed7e15fdc297849a284e211340ccf82fd2fe5c6ae2b15a9f05bbcf24a751a9e8

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.

source=pdf_text observed=2026-08-06T20:25:29.388145Z digest=sha256:56c70177d524c4013b5d7df20f4cbff0588aa795f5a342e8da282123099c3088

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:29.470404Z digest=sha256:62afa0e8b6a81ec23b63f2d0de77b801877d2776bbc148d6a693e5ac58e3828e

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.

source=pdf_text observed=2026-08-06T20:25:29.530529Z digest=sha256:bd76d05223f6c6c4aa8e290543b7985be86b1989d25f470f3117345bcfdaee74

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:29.596127Z digest=sha256:b911eee87a20d49b414b23767fded2b88f09b7107c218ef5107a2a3020f68dae

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:29.687512Z digest=sha256:e1f08975458cb5945309fc42a407b3b22d92cafe42bcebfa8f25dffe1886882e

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.

source=pdf_text observed=2026-08-06T20:25:29.745329Z digest=sha256:0c28a33ba15e144eb5292e93efd669c4e6837b38982df6e549cd112f44425ea2

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:29.817359Z digest=sha256:bed5e1e2f7105d090015663c49311295e28c5e03028365528e3668918bbd5774

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.

source=pdf_text observed=2026-08-06T20:25:29.865938Z digest=sha256:849a873eed4ddcd6c5554be9b1e7b1928f484910301714ea9e6e65a5dab5ee06

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:29.989507Z digest=sha256:daa5d39fffac3cb856a6a74eef0866d8f764d515c167fd085f2a2e35ab114602

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:30.116467Z digest=sha256:21fddd4657a1401e01ef0d58045b7e4147d7e8c5514130d9986705168f2eace3

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:30.269114Z digest=sha256:c4e1167cb2ebe41004f2759c2fd8012db42291e1a34b3800df454c6fd4575da7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:30.383950Z digest=sha256:10717ef9459b5bc4cdb3b2f6a43a56012202c79a8090de62acf7d47516789f43

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:30.515509Z digest=sha256:7c89663bc5ce7e4b338ce19dddc506464fbe7883439277373abf974c4e698c90

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

This paper cites Human Motion Diffusion Model.

Grounding Intelligence in Movement Human Motion Diffusion Model

Reference 80

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:30.631187Z digest=sha256:b185e1f93a5b70105ae2925df750de89fdc9e70aace7c4f5ebf27c4d4d9e22a0

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:30.794697Z digest=sha256:5c586dcd2e63e2e480a8f266e1e1baad274a99e23df309c5a49c9c2db579ef5d

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.

source=pdf_text observed=2026-08-06T20:25:30.904731Z digest=sha256:17db7bb94c772b171365ac3bccde8ef523e5694656aad710427c59c0122e3760

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:31.066330Z digest=sha256:a76a4b9f54b1c6a68220514c06e08687746cf1cfc4ef060fc51ed0a16c8b016b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:31.178290Z digest=sha256:80cee2df57969218e1615221e563fe01e2fe1163410a594fdffb78dc2460c44d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:31.438019Z digest=sha256:bdbdb981d3e1e06c03efac80c8a2495b093781169725e3e25e5e7748ce07b15c

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:31.527216Z digest=sha256:1653b8ed00da851d4f5c98ed7dca7b35e885930cb3fc9c889c741039d9f85fa4

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.

source=pdf_text observed=2026-08-06T20:25:31.588608Z digest=sha256:deb0032f7621d27f1b4fd12af20a564028ad033b8c9357dd752814084c83d190

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:31.654242Z digest=sha256:15cf5208d1ad110441975eac4d3518c1eb04e25a27f6be34632b7af03825f14b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:31.740172Z digest=sha256:692230f8c7e94dd9cf78f0df4c22ae9b8e76b784a94c74b3edbf46f64aad195e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:31.799006Z digest=sha256:597d57602f9a2c318ffb65d1e87250e6bd8e387942a1d238176c7197ef1a10df

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:31.898806Z digest=sha256:55db0d6d8376a77706b7100a4d4291604b6bc2e661699c3e417a863fc04907bb

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:31.963836Z digest=sha256:6bb6cb18ff82a841137fad95699b2a4c1301374b7a578f4262212c80745b9289

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:32.026464Z digest=sha256:1fc621859850edf7d642013ca19c8cb75c0bf6a1cfeb333f46ff437424b4f2a1

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:32.068738Z digest=sha256:eaa4099a230708fab69caf04ca70213dd1588d1f385dbfe5472504252538ce9d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:32.152476Z digest=sha256:88654f85b0645832957add351d2677abbeabd689225d3439c1bdce6bddcad46c

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.

source=pdf_text observed=2026-08-06T20:25:32.219198Z digest=sha256:caab44cf1db19dc3d70c783b1cf4e4eafa53d849007c685c77d677676e4898e5

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:32.332899Z digest=sha256:9b5962b8ad63c8b10bd37b2c022ff2d295982372f9dbc6cedb25b977683de30e

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.

source=pdf_text observed=2026-08-06T20:25:32.433485Z digest=sha256:e1f93951cead6f99ab7b17309f0b96d96b3a7a78acd4d36194c8d1dfab940356

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:32.496941Z digest=sha256:78b243b77fffd46ab63de258f063ba032575ecd9c9ad3a6c5c16989ec3692c93

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:25:32.562488Z digest=sha256:216def7f6e3e8ca75ff47eebee451ee210c6e6ccce1f68a71a4ec37400e8cb3d

Pith citing papers

Observation d7b637b9-b34b-4d17-b00c-657315baf69f · inbound

Zero-Ablation Overstates Register Content Dependence in DINO Vision Transformers cites this paper.

Zero-Ablation Overstates Register Content Dependence in DINO Vision Transformers Grounding Intelligence in Movement

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:00:24.721382Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-10T12:56:32.421877Z digest=sha256:a5961545ec5810703ae1fd2fd5e0bb54d368f9d9eae1a8d819c7c84590b359b3