Paper Citation Record · LEDGER

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement

As of 13 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 1 inbound Pith citation observation for arXiv:2411.17764.

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

pith.paper-citation-record.v1
2411.17764 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

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measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T21:57:15.285757Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T22:00:41.924058Z

Reference resolution

49 of 49 outbound references displayed

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External citation measurements

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Outbound references

Observation 19ecd7f7-c150-4da4-9afa-467d9eef3a44 · outbound

This paper cites an unresolved cited work.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Unresolved cited work

Reference 1

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Observation 11dd6156-200d-4326-8beb-5c8979e7f81a · outbound

This paper cites Learning reward functions for robotic manipulation by observ- ing humans, 2023.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Learning reward functions for robotic manipulation by observ- ing humans, 2023

Reference 2

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Observation b83cd651-b7cc-41d5-b329-d6d0bcc33a1c · outbound

This paper cites Human-to-Robot Imitation in the Wild.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Human-to-Robot Imitation in the Wild

Reference 3

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Observation 5c812fbd-383b-46b2-9b55-153ca65ac008 · outbound

This paper cites Video pre- training (VPT): Learning to act by watching unlabeled online videos.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Video pre- training (VPT): Learning to act by watching unlabeled online videos

Reference 4

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Observation e05c97db-108e-459b-97a6-8d1941bf3494 · outbound

This paper cites The perils of trial-and-error reward design: Misdesign through overfitting and invalid task specifications.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement The perils of trial-and-error reward design: Misdesign through overfitting and invalid task specifications

Reference 5

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Observation bb7f932b-2ae9-4327-83b2-b5baf845e580 · outbound

This paper cites Scaling ego- centric vision: The EPIC-KITCHENS dataset.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Scaling ego- centric vision: The EPIC-KITCHENS dataset

Reference 6

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Observation ee15b13c-1732-4860-8815-935e210c386a · outbound

This paper cites Rescaling egocentric vision: Collection, pipeline and challenges for EPIC-KITCHENS-100.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Rescaling egocentric vision: Collection, pipeline and challenges for EPIC-KITCHENS-100

Reference 7

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Observation 82e1517c-2e2f-4a9e-8371-aa9d3e544c37 · outbound

This paper cites Video predic- tion models as rewards for reinforcement learning.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Video predic- tion models as rewards for reinforcement learning

Reference 8

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Observation 711d2e16-250e-481b-b1eb-14581d5bf553 · outbound

This paper cites Contrastive learning as goal-conditioned reinforcement learning,.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Contrastive learning as goal-conditioned reinforcement learning,

Reference 9

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Observation 908bc309-970b-4a76-a7ae-68e01e0dd785 · outbound

This paper cites Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization

Reference 10

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Observation 944a3854-6209-45e7-8593-b15ea686d2a2 · outbound

This paper cites Learning Robust Rewards with Adversarial Inverse Reinforcement Learning.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Learning Robust Rewards with Adversarial Inverse Reinforcement Learning

Reference 11

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Observation da74d825-d443-43a8-bd2a-f30e958f31b7 · outbound

This paper cites Domain- adversarial training of neural networks.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Domain- adversarial training of neural networks

Reference 12

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Observation 963ddfdb-43cb-4490-ae74-5e8ac04635fb · outbound

This paper cites Generative adversarial nets.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Generative adversarial nets

Reference 13

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Observation 5f248316-4948-4d16-b633-39295f429797 · outbound

This paper cites Ego4D: Around the world in 3,000 hours of egocentric video.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Ego4D: Around the world in 3,000 hours of egocentric video

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.813695Z

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Observation 0c25a2c0-35f0-4577-acf5-a791b0b5542b · outbound

This paper cites Inverse reward design.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Inverse reward design

Reference 15

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Observation de714324-14be-4d2a-87e0-ef81573709ea · outbound

This paper cites Deep residual learning for image recognition.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Deep residual learning for image recognition

Reference 16

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Source-reported events for the cited work

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Observation d94d9fea-05f5-42da-a25e-4c1a199c4a68 · outbound

This paper cites Generative adver- sarial imitation learning.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Generative adver- sarial imitation learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.776858Z

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Observation 5d735659-4254-420a-b394-07e71a116252 · outbound

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PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Generative Adversarial Imitation Learning

Reference 18

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Observation 4177153f-b177-4552-a35b-723fa3cd5a81 · outbound

This paper cites Diffusion Reward: Learning Rewards via Conditional Video Diffusion.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Diffusion Reward: Learning Rewards via Conditional Video Diffusion

Reference 19

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Observation ba02e57a-0222-4fd8-99ee-4cd0ed8209a7 · outbound

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PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Auto-Encoding Variational Bayes

Reference 20

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Observation 3b900e1a-230b-4a4d-ba7b-797012caff4b · outbound

This paper cites InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations

Reference 21

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This paper cites VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training

Reference 22

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This paper cites 9 Vip: Towards universal visual reward and representa- tion via value-implicit pre-training, 2023.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement 9 Vip: Towards universal visual reward and representa- tion via value-implicit pre-training, 2023

Reference 23

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Observation 04eab034-e282-4624-9b20-0fd582b6e75a · outbound

This paper cites Towards Theoretical Understanding of Inverse Reinforcement Learning.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Towards Theoretical Understanding of Inverse Reinforcement Learning

Reference 24

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Observation 246b6b1a-a689-4a57-aa9b-a2a9b7a97eb5 · outbound

This paper cites R3M: A Universal Visual Representation for Robot Manipulation.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement R3M: A Universal Visual Representation for Robot Manipulation

Reference 26

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This paper cites Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reference 27

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Observation ecd888a8-d3b6-4ca2-bbc9-1fbec814783c · outbound

This paper cites Reinforcement learning by reward-weighted regression for operational space control.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Reinforcement learning by reward-weighted regression for operational space control

Reference 28

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Observation 357bb53a-dc1d-43ca-8bbc-c6a30e6aa68e · outbound

This paper cites DexMV: Imitation learning for dexterous manipula- tion from human videos.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement DexMV: Imitation learning for dexterous manipula- tion from human videos

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.739943Z

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This paper cites Artificial Intelli- gence: A Modern Approach.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Artificial Intelli- gence: A Modern Approach

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.727545Z

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This paper cites Time-contrastive networks: Self-supervised learning from video.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Time-contrastive networks: Self-supervised learning from video

Reference 31

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This paper cites Time-contrastive networks: Self-supervised learning from video, 2018.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Time-contrastive networks: Self-supervised learning from video, 2018

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.701581Z

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This paper cites Lewis, and Andrew G.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Lewis, and Andrew G

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.688946Z

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Observation 6d51ecbd-82a2-4075-97eb-1b64fc379c50 · outbound

This paper cites Reinforcement Learning: An Introduction.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Reinforcement Learning: An Introduction

Reference 34

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Observation 936a2caa-1bd3-4ba7-a870-c0edf194c34f · outbound

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PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement DeepMind Control Suite

Reference 35

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This paper cites Wozniak, Andrea Gasparri, and Danica Kragic.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Wozniak, Andrea Gasparri, and Danica Kragic

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.664342Z

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This paper cites Maximum entropy deep inverse reinforcement learning, 2016.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Maximum entropy deep inverse reinforcement learning, 2016

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.651501Z

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This paper cites Rank2Reward: Learning Shaped Reward Functions from Passive Video.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Rank2Reward: Learning Shaped Reward Functions from Passive Video

Reference 38

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This paper cites Representation Matters: Offline Pretraining for Sequential Decision Making.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Representation Matters: Offline Pretraining for Sequential Decision Making

Reference 39

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This paper cites Im- age augmentation is all you need: Regularizing deep reinforcement learning from pixels.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Im- age augmentation is all you need: Regularizing deep reinforcement learning from pixels

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.638107Z

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This paper cites Meta-World: A benchmark and evaluation for multi-task and meta reinforcement learning.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Meta-World: A benchmark and evaluation for multi-task and meta reinforcement learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.625289Z

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This paper cites Learning to drive by watching YouTube videos: Action-conditioned contrastive policy pretraining.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Learning to drive by watching YouTube videos: Action-conditioned contrastive policy pretraining

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.612159Z

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Observation c9badd64-d63e-4c23-ac7c-b2f32411452a · outbound

This paper cites Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Reference 43

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This paper cites Ziebart, Andrew Maas, J.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Ziebart, Andrew Maas, J

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.598736Z

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PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Unresolved cited work

Reference 46

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PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Unresolved cited work

Reference 47

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Observation dc209de8-e71d-49c8-b68d-be4ee4327b38 · outbound

This paper cites Robotic Experiment Setup The real-robot experiments are performed using a Universal Robots UR5 robot arm equipped with a Robotiq 3-Finger Gripper (Figure 8).

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Robotic Experiment Setup The real-robot experiments are performed using a Universal Robots UR5 robot arm equipped with a Robotiq 3-Finger Gripper (Figure 8)

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.559402Z

Source-reported events for the cited work

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Observation d005df41-9d71-4167-b01f-87516338559a · outbound

This paper cites The case of β = 0(PROGRESSOR with- out Push-back) is discussed in the main paper.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement The case of β = 0(PROGRESSOR with- out Push-back) is discussed in the main paper

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.546314Z

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Observation 5422f123-94a9-4e8a-b7a6-299b5d1cba3a · outbound

This paper cites This figure serves as an extension to Figure 7 for complete- ness.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement This figure serves as an extension to Figure 7 for complete- ness

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:37:10.533313Z

Source-reported events for the cited work

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Observation d855ac28-3147-47c0-9bba-c525d45f80fb · outbound

This paper cites an unresolved cited work.

PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement Unresolved cited work

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TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance cites this paper.

TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance PROGRESSOR: A Perceptually Guided Reward Estimator with Self-Supervised Online Refinement

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