Paper Citation Record · LEDGER

Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation

As of 9 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2607.13938.

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

pith.paper-citation-record.v1
2607.13938 v1

Coverage vector

measured 50 of 50 reference resolution

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Reference resolution

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Outbound references

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Unresolved cited work

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Abbeel and A

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Abbeel, A

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Torabi, G

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Garc ˜Aa and F

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Lederer, E

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Behavioral Cloning from Observation

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Observation 7efaa156-18a6-401a-a115-1596d296c7b6 · outbound

This paper cites Neural Control Barrier Functions for Safe Navigation.

Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Neural Control Barrier Functions for Safe Navigation

Reference 14

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Walking in Narrow Spaces: Safety-critical Locomotion Control for Quadrupedal Robots with Duality-based Optimization

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Lipschitz Continuity of Signal Temporal Logic Robustness Measures: Synthesizing Control Barrier Functions from One Expert Demonstration

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Advances in the Theory of Control Barrier Functions: Addressing Practical Challenges in Safe Control Synthesis for Autonomous and Robotic Systems

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Zhang, O

Reference 18

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Agrawal and K

Reference 19

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This paper cites Learning Control Barrier Functions and their application in Reinforcement Learning: A Survey.

Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Learning Control Barrier Functions and their application in Reinforcement Learning: A Survey

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Unresolved cited work

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Srinivasan, A

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Robey, H

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Safe Inverse Reinforcement Learning via Control Barrier Function

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Nakamura, A

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Tabbara and H

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Tayal, M

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Jang, G.-H

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Learning Risk-Aware Costmaps via Inverse Reinforcement Learning for Off-Road Navigation

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Ho and S

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Improved Training of Wasserstein GANs

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Orsini, A

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation MuSHR: A Low-Cost, Open-Source Robotic Racecar for Education and Research

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Wasserstein GAN

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Mitchell, A

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation Generative Adversarial Imitation from Observation

Reference 2019

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation How to Train Your Neural Control Barrier Function: Learning Safety Filters for Complex Input-Constrained Systems

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Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation doi:10.1109/tro.2025.3530348

Reference 2025

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