Paper Citation Record · LEDGER

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics

As of 15 August 2026, this Paper Citation Record lists 76 of 76 outbound references and 2 inbound Pith citation observations for arXiv:2412.09584.

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

pith.paper-citation-record.v1
2412.09584 v3

Coverage vector

measured 76 of 76 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:57:34.280379Z

measured 78 of 78 standing notices

One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T22:10:50.600849Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T22:13:59.872724Z

Reference resolution

76 of 76 outbound references displayed

verified exact4
verified fuzzy42
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7ff5cd90-e025-4f27-9dc9-a360bcdf933d · outbound

This paper cites write newline.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics write newline

Reference 1

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Observation 0d0d13f7-473c-46d2-aea1-5495d0fb196e · outbound

This paper cites Learning to Poke by Poking: Experiential Learning of Intuitive Physics.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Learning to Poke by Poking: Experiential Learning of Intuitive Physics

Reference 2

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Observation 4ce70902-5d8a-439e-9f8f-40503af4816b · outbound

This paper cites Strong mixed-integer programming formulations for trained neural networks.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Strong mixed-integer programming formulations for trained neural networks

Reference 3

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Observation 2159f7be-f093-4224-bcfb-200a6f1e5c59 · outbound

This paper cites The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results

Reference 4

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This paper cites Interaction networks for learning about objects, relations and physics.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Interaction networks for learning about objects, relations and physics

Reference 5

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Unresolved cited work

Reference 6

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Unresolved cited work

Reference 7

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Unresolved cited work

Reference 8

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Unresolved cited work

Reference 9

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Observation f77f3097-c418-4be0-a257-73050d15a4b1 · outbound

This paper cites Model Predictive Control.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Model Predictive Control

Reference 10

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Observation ad66ddba-b4cd-4368-af0c-dedda126099b · outbound

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Unresolved cited work

Reference 11

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Observation ad9e6d37-2f7a-4165-b3af-1baee465b232 · outbound

This paper cites Learning multi-object dynamics with compositional neural radiance fields.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Learning multi-object dynamics with compositional neural radiance fields

Reference 12

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Observation bc2009e3-b14f-416d-be03-e3a90668685c · outbound

This paper cites Self-supervised visual planning with temporal skip connections.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Self-supervised visual planning with temporal skip connections

Reference 13

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Observation b6afa201-918d-443b-adeb-28534bd4142d · outbound

This paper cites Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control

Reference 14

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Observation 1c70ecc1-4a03-4036-b47f-8f04b190b188 · outbound

This paper cites Zico Kolter Eric Wong.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Zico Kolter Eric Wong

Reference 15

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Observation 076d0aba-ffd1-4872-8f59-fa2e7275a2cb · outbound

This paper cites Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound

Reference 16

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Observation 9b041906-bdb6-454e-adc2-dfdb5b818477 · outbound

This paper cites Deep visual foresight for planning robot motion.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Deep visual foresight for planning robot motion

Reference 17

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Observation bf9e586a-0771-4565-b8f3-93650911ccc8 · outbound

This paper cites Unsupervised Learning for Physical Interaction through Video Prediction.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Unsupervised Learning for Physical Interaction through Video Prediction

Reference 18

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Observation 4687bcb2-8b64-40a6-8ddc-7fa75281c23b · outbound

This paper cites On the effectiveness of interval bound propagation for training verifiably robust models.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics On the effectiveness of interval bound propagation for training verifiably robust models

Reference 19

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Observation 99b06a9c-3f9f-4e44-af2b-2b0aac78e972 · outbound

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Towards Tight Convex Relaxations for Contact-Rich Manipulation

Reference 20

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Observation 709e7e81-5aef-44c1-9cfd-450bb0abc55d · outbound

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Dream to Control: Learning Behaviors by Latent Imagination

Reference 21

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Observation 3a5ab64d-3f90-4703-99b6-adaa6827c3f9 · outbound

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Learning latent dynamics for planning from pixels

Reference 22

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Observation 4199a90b-73eb-4951-accf-2eddec374fbf · outbound

This paper cites Learning latent dynamics for planning from pixels.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Learning latent dynamics for planning from pixels

Reference 23

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Observation 6622dd3b-1b22-4b6b-9a94-969d720447b2 · outbound

This paper cites Model predictive control for aggressive driving over uneven terrain, 2024.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Model predictive control for aggressive driving over uneven terrain, 2024

Reference 24

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This paper cites Real-time safe control of neural network dynamic models with sound approximation, 2024 a.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Real-time safe control of neural network dynamic models with sound approximation, 2024 a

Reference 25

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Observation 0c047bf5-187c-4696-a726-6f261e5a2bf4 · outbound

This paper cites Verification of neural control barrier functions with symbolic derivative bounds propagation.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Verification of neural control barrier functions with symbolic derivative bounds propagation

Reference 26

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This paper cites Mesh-based dynamics model with occlusion reasoning for cloth manipulation.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Mesh-based dynamics model with occlusion reasoning for cloth manipulation

Reference 27

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Towards scalable complete verification of relu neural networks via dependency-based branching

Reference 28

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Observation 63e423db-daa4-428e-82cc-470ed2841c94 · outbound

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Unsupervised learning of object keypoints for perception and control

Reference 29

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Observation d66dfdd4-3026-4912-b1ad-425fbd952654 · outbound

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Learning quadrupedal locomotion over challenging terrain

Reference 30

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Observation 9bc74460-1690-4b13-a7d9-fb385f9aa317 · outbound

This paper cites Deepmpc: Learning deep latent features for model predictive control.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Deepmpc: Learning deep latent features for model predictive control

Reference 31

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids

Reference 32

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Source-reported events for the cited work

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Propagation networks for model-based control under partial observation

Reference 33

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Causal discovery in physical systems from videos

Reference 34

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Learning visible connectivity dynamics for cloth smoothing

Reference 35

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Kochenderfer

Reference 36

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Model-based control with sparse neural dynamics

Reference 37

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Observation 35f463e5-f525-432c-bae6-23fc4dd4640d · outbound

This paper cites Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control

Reference 38

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Pawan Kumar

Reference 39

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Unified particle physics for real-time applications

Reference 40

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning

Reference 41

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Graphs of Convex Sets with Applications to Optimal Control and Motion Planning

Reference 42

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Observation 7f1bfea7-c9fb-477e-8cca-3ff846e5952f · outbound

This paper cites The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results

Reference 43

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Source-reported events for the cited work

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BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Deep dynamics models for learning dexterous manipulation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:35.133241Z

Source-reported events for the cited work

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Observation b941eae5-2021-43d6-9276-855ae932927e · outbound

This paper cites Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Improved Branch and Bound for Neural Network Verification via Lagrangian Decomposition

Reference 45

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This paper cites The cross-entropy method: a unified approach to combinatorial optimization, Monte-Carlo simulation and machine learning.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics The cross-entropy method: a unified approach to combinatorial optimization, Monte-Carlo simulation and machine learning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:35.118770Z

Source-reported events for the cited work

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Observation 493a03f9-e380-4d09-a7a1-f6b2b2ae2463 · outbound

This paper cites Deep model predictive optimization, 2023.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Deep model predictive optimization, 2023

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:35.103872Z

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Observation 6af12bd1-0483-4061-af99-1771ba0782c2 · outbound

This paper cites A convex relaxation barrier to tight robustness verification of neural networks.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics A convex relaxation barrier to tight robustness verification of neural networks

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:35.089116Z

Source-reported events for the cited work

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Observation 82c369d5-04b2-463f-a8cb-bc5361483ce3 · outbound

This paper cites Mastering atari, go, chess and shogi by planning with a learned model.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Mastering atari, go, chess and shogi by planning with a learned model

Reference 49

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Source-reported events for the cited work

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This paper cites Masked world models for visual control.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Masked world models for visual control

Reference 50

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Observation af0ddc30-0f24-498c-bf93-29c7b2aaa6e7 · outbound

This paper cites RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T16:57:34.165372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 554d959f-fcf9-4d0c-9b9e-dd03c0d39e65 · outbound

This paper cites Robocook: Long-horizon elasto-plastic object manipulation with diverse tools, 2023.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Robocook: Long-horizon elasto-plastic object manipulation with diverse tools, 2023

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T16:57:34.169867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 574322da-2ec1-486d-8308-d1424e902738 · outbound

This paper cites An abstract domain for certifying neural networks.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics An abstract domain for certifying neural networks

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:35.045600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 23791380-e26c-4be2-8dbd-d8b67fe0217e · outbound

This paper cites The Surprising Effectiveness of Linear Models for Visual Foresight in Object Pile Manipulation.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics The Surprising Effectiveness of Linear Models for Visual Foresight in Object Pile Manipulation

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-08-11T16:57:34.595848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1f05736c-9946-4cd3-8b8f-65f1d30e82cc · outbound

This paper cites Manipulation by feel: Touch-based control with deep predictive models.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Manipulation by feel: Touch-based control with deep predictive models

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:35.030830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 509ae298-1650-407c-9633-19397c911c0c · outbound

This paper cites Evaluating robustness of neural networks with mixed integer programming, 2019.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Evaluating robustness of neural networks with mixed integer programming, 2019

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T16:57:34.188179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff57a165-d0ff-48b9-af18-eaacba13bb2c · outbound

This paper cites Efficient formal safety analysis of neural networks.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Efficient formal safety analysis of neural networks

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:35.003132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 636280a7-62e2-4093-9473-e82db7c4defd · outbound

This paper cites Beta-crown: Efficient bound propagation with per-neuron split constraints for complete and incomplete neural network robustness verification.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Beta-crown: Efficient bound propagation with per-neuron split constraints for complete and incomplete neural network robustness verification

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.986749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 73baaace-e175-49b1-aa0d-322264d77d58 · outbound

This paper cites Dynamic-Resolution Model Learning for Object Pile Manipulation.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Dynamic-Resolution Model Learning for Object Pile Manipulation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-11T16:57:34.201516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04fba992-0ed1-4f54-a8a0-91ec4b1c88e6 · outbound

This paper cites Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-11T16:57:34.205893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6481e41c-79ad-4606-8345-bd166cd96b2d · outbound

This paper cites Safe control with neural network dynamic models, 2022.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Safe control with neural network dynamic models, 2022

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.970929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2c4f2018-eda6-4e21-b02a-12e18a7b8882 · outbound

This paper cites Model predictive path integral control: From theory to parallel computation.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Model predictive path integral control: From theory to parallel computation

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.956290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2b3a95bd-7fa2-419c-82b0-5b05a16ed0b0 · outbound

This paper cites Verified Safe Reinforcement Learning for Neural Network Dynamic Models.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Verified Safe Reinforcement Learning for Neural Network Dynamic Models

Reference 63

Resolution: verified exact; local_arxiv, observed 2026-08-11T16:57:34.556522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 39474ca8-b450-409d-ad3c-96cfe375469d · outbound

This paper cites Daydreamer: World models for physical robot learning.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Daydreamer: World models for physical robot learning

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.941266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 05f2a9ad-ac94-4a13-8c15-38aef51ca873 · outbound

This paper cites Fast and complete: Enabling complete neural network verification with rapid and massively parallel incomplete verifiers.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Fast and complete: Enabling complete neural network verification with rapid and massively parallel incomplete verifiers

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.926154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e48fb5d9-f613-4d0b-9efd-ded78bab0140 · outbound

This paper cites Experience-embedded visual foresight.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Experience-embedded visual foresight

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.910999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation eba2313f-2ad2-4f21-9c67-d06bad64ac6b · outbound

This paper cites Covo-mpc: Theoretical analysis of sampling-based mpc and optimal covariance design, 2024.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Covo-mpc: Theoretical analysis of sampling-based mpc and optimal covariance design, 2024

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.894838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b146d410-3b3e-4318-92a9-d9f9390c00de · outbound

This paper cites Trajectory distribution control for model predictive path integral control using covariance steering.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Trajectory distribution control for model predictive path integral control using covariance steering

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T16:57:34.242194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 618e2245-8a74-436f-8cad-68e8feb99d5a · outbound

This paper cites Efficient neural network robustness certification with general activation functions.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Efficient neural network robustness certification with general activation functions

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.880328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fd2a7a4e-eaa5-4d57-af24-c5b73d042a8f · outbound

This paper cites General cutting planes for bound-propagation-based neural network verification.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics General cutting planes for bound-propagation-based neural network verification

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.865694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c3d9b8cf-bf32-4882-83fd-1b6c1bab0c2c · outbound

This paper cites A branch and bound framework for stronger adversarial attacks of R e LU networks.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics A branch and bound framework for stronger adversarial attacks of R e LU networks

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.850969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 06927cc0-e36b-4793-94cb-f4ca669d2437 · outbound

This paper cites Adaptigraph: Material-adaptive graph-based neural dynamics for robotic manipulation.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Adaptigraph: Material-adaptive graph-based neural dynamics for robotic manipulation

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:57:34.835676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b753a7ff-908a-4b6d-ab24-b95e7404bed4 · outbound

This paper cites A Simple Decentralized Cross-Entropy Method.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics A Simple Decentralized Cross-Entropy Method

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-08-11T16:57:34.458431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ba144938-1f75-4137-8d29-8a19af782741 · outbound

This paper cites @esa (Ref.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics @esa (Ref

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-11T16:57:34.269838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12720a3b-05b0-4d96-a020-3f0178e67762 · outbound

This paper cites an unresolved cited work.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Unresolved cited work

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-11T16:57:34.275198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95e2065f-c5a6-45c2-b923-d8cb4ee9d03a · outbound

This paper cites 0 ” stands for taking positive elements from the matrix while setting other elements to zero, and vice versa for subscript “ <0.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics 0 ” stands for taking positive elements from the matrix while setting other elements to zero, and vice versa for subscript “ <0

Reference 76

Resolution: malformed identifier; no resolver link, observed 2026-08-11T16:57:34.280379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 69564ba2-6d51-451c-b8cf-04cf363277e5 · inbound

Parallel Differentiable Reachability for Learning and Planning with Certified Neural Dynamics and Controllers cites this paper.

Parallel Differentiable Reachability for Learning and Planning with Certified Neural Dynamics and Controllers BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-06-29T22:13:59.874537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c58ba40b-0e6c-476f-be1f-d6a30d826458 · inbound

Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial cites this paper.

Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-06-29T16:23:39.426892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.