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Paper Citation Record · LEDGER

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment

As of 9 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2602.01515.

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

pith.paper-citation-record.v1
2602.01515 v2

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:44:28.867239Z

measured 27 of 27 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

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Outbound references

Observation e5a6e3a1-78bd-4a48-986d-46a3fe7b2a62 · outbound

This paper cites Safe reinforcement learning via shielding.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Safe reinforcement learning via shielding

Reference 1

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Observation ad2f2442-31aa-48be-af76-e0dfe918b155 · outbound

This paper cites Safe model-based reinforcement learning with stability guarantees.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Safe model-based reinforcement learning with stability guarantees

Reference 2

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Observation 9cf67001-48fe-41a6-8fcc-4ede816c038e · outbound

This paper cites Safe learning in robotics: From learning-based control to safe reinforcement learning.Annual Review of Control, Robotics, and Autonomous Systems, 5:411–444, 2022.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Safe learning in robotics: From learning-based control to safe reinforcement learning.Annual Review of Control, Robotics, and Autonomous Systems, 5:411–444, 2022

Reference 3

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Observation 45fb5b55-7bed-4bd3-b1b7-da7768298c07 · outbound

This paper cites End-to-end safe reinforcement learning through barrier functions for safety-critical continuous control tasks.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment End-to-end safe reinforcement learning through barrier functions for safety-critical continuous control tasks

Reference 4

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source=pdf_text observed=2026-08-03T05:44:27.404031Z digest=sha256:56beabfe16357e98e11ca62125c9425d98632927ec291a0584ea35f6d3371c5d

Observation 5ca2cbc8-6068-482c-80d0-f44fd4728602 · outbound

This paper cites Lyapunov-based Safe Policy Optimization for Continuous Control.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Lyapunov-based Safe Policy Optimization for Continuous Control

Reference 5

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source=pdf_text observed=2026-08-03T05:44:27.437584Z digest=sha256:ee1ee7d90640a36e558c4d88b43d9fee5986b835d5af9c39692352c142ac7c5c

Observation 5330e68d-682b-4add-89a3-e2d18bfa6570 · outbound

This paper cites Pronav: Propriocep- tive traversability estimation for legged robot navigation in outdoor environments.IEEE Robotics and Automation Letters, 9(8):7190–7197, 2024.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Pronav: Propriocep- tive traversability estimation for legged robot navigation in outdoor environments.IEEE Robotics and Automation Letters, 9(8):7190–7197, 2024

Reference 6

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Observation 958cc24a-3801-40d7-b61d-88b9ccd251df · outbound

This paper cites Recurrent world models facilitate policy evolution.Advances in neural information processing systems, 31, 2018.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Recurrent world models facilitate policy evolution.Advances in neural information processing systems, 31, 2018

Reference 7

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source=pdf_text observed=2026-08-03T05:44:27.576694Z digest=sha256:d540076e5a18dbf03be242ff107a5deb63cdb88259ef0cd72e556c2ca204284e

Observation a95ffc65-3ad4-4133-979d-d828dd3dc82f · outbound

This paper cites Out-of-distribution detection for reinforcement learning agents with proba- bilistic dynamics models.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Out-of-distribution detection for reinforcement learning agents with proba- bilistic dynamics models

Reference 8

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Observation 78fcf487-158b-45f2-8775-cc4601d7f3b1 · outbound

This paper cites Can you trust your agent? the effect of out-of-distribution detection on the safety of reinforcement learning systems.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Can you trust your agent? the effect of out-of-distribution detection on the safety of reinforcement learning systems

Reference 9

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Observation 9b186808-83da-4fba-adb7-16b43e7c5a4f · outbound

This paper cites Model-free robot anomaly detection.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Model-free robot anomaly detection

Reference 10

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Observation 889680a5-4564-438c-90ca-d0e9f05fdc94 · outbound

This paper cites Reaching in clutter with whole-arm tactile sensing.The International Journal of Robotics Research, 32(4):458–482, 2013.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Reaching in clutter with whole-arm tactile sensing.The International Journal of Robotics Research, 32(4):458–482, 2013

Reference 11

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Observation 61d4f2b9-ebb3-4ba1-94cd-6a6cbefadf2c · outbound

This paper cites Rethinking out-of-distribution (ood) detection: Masked image modeling is all you need.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Rethinking out-of-distribution (ood) detection: Masked image modeling is all you need

Reference 12

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Observation e0735422-dde4-445c-ae08-54733a7b07fc · outbound

This paper cites Isola- tion forest.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Isola- tion forest

Reference 13

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Observation 3f5ff856-b6f7-4dfc-8e68-27033f70ce5e · outbound

This paper cites Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning

Reference 14

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Observation 697355c3-412a-42bf-a7b4-3ca69bd9c1a9 · outbound

This paper cites Scalable multi-objective robot reinforcement learning through gradient conflict resolution.arXiv:2509.14816, 2025.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Scalable multi-objective robot reinforcement learning through gradient conflict resolution.arXiv:2509.14816, 2025

Reference 15

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Observation 18b70f30-7388-4ded-8125-6176789f1e7d · outbound

This paper cites Whole-Body Dynamic Throwing with Legged Manipulators.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Whole-Body Dynamic Throwing with Legged Manipulators

Reference 16

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Observation 9f6d02a6-17de-4e18-a906-be498243e7ad · outbound

This paper cites Deep dynamics models for learning dex- terous manipulation.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Deep dynamics models for learning dex- terous manipulation

Reference 17

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Observation 365574e5-b5e4-465f-b085-25944645f582 · outbound

This paper cites Do Deep Generative Models Know What They Don't Know?.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Do Deep Generative Models Know What They Don't Know?

Reference 18

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Observation 21b075b6-02b0-4767-abf5-a3ab284059a8 · outbound

This paper cites Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection

Reference 19

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Observation f143972c-56af-4c4f-aa0a-35e11f7b93e7 · outbound

This paper cites Variational inference mpc for bayesian model-based reinforcement learning.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Variational inference mpc for bayesian model-based reinforcement learning

Reference 20

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Observation 2afd56a1-9ab4-42a3-a0de-274976869e31 · outbound

This paper cites A multimodal anomaly detector for robot-assisted feed- ing using an lstm-based variational autoencoder.IEEE Robotics and Automation Letters, 3(3):1544–1551, 2018.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment A multimodal anomaly detector for robot-assisted feed- ing using an lstm-based variational autoencoder.IEEE Robotics and Automation Letters, 3(3):1544–1551, 2018

Reference 21

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Observation af472da0-e43b-4984-b4cf-954ffe533503 · outbound

This paper cites Guaranteeing out-of-distribution detec- tion in deep rl via transition estimation.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Guaranteeing out-of-distribution detec- tion in deep rl via transition estimation

Reference 22

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Observation 3fb170bf-7165-4c60-9d80-388790a3f08a · outbound

This paper cites Deep one-class classification.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Deep one-class classification

Reference 23

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Observation 2b3b64a2-9aee-4142-b87f-15d906f9c03b · outbound

This paper cites Mamba Adaptive Anomaly Transformer with association discrepancy for time series.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Mamba Adaptive Anomaly Transformer with association discrepancy for time series

Reference 24

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Observation 1e1d5c8c-1243-4384-adc3-ce99cd525380 · outbound

This paper cites unitree rl lab: Reinforcement learning implementation for unitree robots based on isaaclab.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment unitree rl lab: Reinforcement learning implementation for unitree robots based on isaaclab

Reference 25

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Observation 3d78225e-7665-4e8a-9352-6f0b6927993c · outbound

This paper cites Extracting and composing robust features with denoising autoencoders.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Extracting and composing robust features with denoising autoencoders

Reference 26

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Observation 4a646393-9f7b-4bd4-a356-b3c95c38f3c7 · outbound

This paper cites Patchad: A lightweight patch-based mlp-mixer for time series anomaly detection.IEEE Transactions on Big Data, 2025.

RAPT: Model-Predictive Out-of-Distribution Detection and Failure Diagnosis for Sim-to-Real Humanoid Deployment Patchad: A lightweight patch-based mlp-mixer for time series anomaly detection.IEEE Transactions on Big Data, 2025

Reference 27

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Pith citing papers

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