Paper Citation Record · LEDGER

A Survey of State Representation Learning for Deep Reinforcement Learning

As of 20 August 2026, this Paper Citation Record lists 100 of 157 outbound references and 7 inbound Pith citation observations for arXiv:2506.17518.

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

pith.paper-citation-record.v1
2506.17518 v1

Coverage vector

measured 100 of 157 reference resolution

Typed states for the displayed outbound observations.

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measured 107 of 107 standing notices

One-hop event checks from named stored sources.

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measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:48:43.522343Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T07:59:40.694649Z

Reference resolution

100 of 157 outbound references displayed

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External citation measurements

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Outbound references

Observation fc0284af-a214-4ae6-bd9a-17278f658440 · outbound

This paper cites A Theory of Abstraction in Reinforcement Learning.

A Survey of State Representation Learning for Deep Reinforcement Learning A Theory of Abstraction in Reinforcement Learning

Reference 1

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Observation 7fbfffcb-2458-40b7-a767-c8b2f8e4502d · outbound

This paper cites Machado, Pablo Samuel Castro, and Marc G Bellemare.

A Survey of State Representation Learning for Deep Reinforcement Learning Machado, Pablo Samuel Castro, and Marc G Bellemare

Reference 2

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Observation 70c79a2a-a6f7-400c-8d9c-9cac30786a7d · outbound

This paper cites Bellemare.

A Survey of State Representation Learning for Deep Reinforcement Learning Bellemare

Reference 3

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Observation 683c03af-f7ca-44e0-96ef-bbf2d68e1bd0 · outbound

This paper cites Proto Successor Measure: Representing the Behavior Space of an RL Agent.

A Survey of State Representation Learning for Deep Reinforcement Learning Proto Successor Measure: Representing the Behavior Space of an RL Agent

Reference 4

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Observation 9bebbd1f-1e5a-4262-86dd-9ec8928f9ab0 · outbound

This paper cites Alemi, Ian Fischer, Joshua V.

A Survey of State Representation Learning for Deep Reinforcement Learning Alemi, Ian Fischer, Joshua V

Reference 5

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Observation adedad9f-34c0-4fde-b579-135587ad0138 · outbound

This paper cites Learning markov state abstractions for deep reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Learning markov state abstractions for deep reinforcement learning

Reference 6

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Observation b3b1068e-a4d9-487b-bee4-7c892d5c1c0f · outbound

This paper cites A recipe for unbounded data augmentation in visual reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning A recipe for unbounded data augmentation in visual reinforcement learning

Reference 7

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Observation ffa5f726-b3d2-4455-a861-9d7d46f2316e · outbound

This paper cites Unsupervised State Representation Learning in Atari.

A Survey of State Representation Learning for Deep Reinforcement Learning Unsupervised State Representation Learning in Atari

Reference 8

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Observation 1fb18abd-062d-4b92-a5b8-2b513c57520f · outbound

This paper cites Hindsight experience replay.

A Survey of State Representation Learning for Deep Reinforcement Learning Hindsight experience replay

Reference 9

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Observation 40eb1f6f-2920-43d9-a758-ecf0e3cb527f · outbound

This paper cites Self-supervised learning from images with a joint-embedding predictive architecture.

A Survey of State Representation Learning for Deep Reinforcement Learning Self-supervised learning from images with a joint-embedding predictive architecture

Reference 10

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Observation 9f2277d9-3556-4ae1-904b-9a1fe1c9f621 · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

A Survey of State Representation Learning for Deep Reinforcement Learning Neural Machine Translation by Jointly Learning to Align and Translate

Reference 11

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Observation b52123de-b84a-4f66-bcd7-9f470184f823 · outbound

This paper cites VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning.

A Survey of State Representation Learning for Deep Reinforcement Learning VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

Reference 12

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Observation c6e9439b-652b-4a2f-9c31-bc0b655ce9d1 · outbound

This paper cites Combining Reconstruction and Contrastive Methods for Multimodal Representations in RL.

A Survey of State Representation Learning for Deep Reinforcement Learning Combining Reconstruction and Contrastive Methods for Multimodal Representations in RL

Reference 13

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Observation e00709d0-3b7e-4178-bb9a-6bc6f9229e38 · outbound

This paper cites The arcade learning environment: An evaluation platform for general agents.

A Survey of State Representation Learning for Deep Reinforcement Learning The arcade learning environment: An evaluation platform for general agents

Reference 14

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Observation 227c9b5b-29aa-4cf5-ba90-48338c9f003b · outbound

This paper cites Representation Learning: A Review and New Perspectives.

A Survey of State Representation Learning for Deep Reinforcement Learning Representation Learning: A Review and New Perspectives

Reference 15

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This paper cites Look where you look! saliency-guided q-networks for generalization in visual reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Look where you look! saliency-guided q-networks for generalization in visual reinforcement learning

Reference 16

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Observation 6a57f70d-d1ec-4662-ab92-de6fed824494 · outbound

This paper cites Riedmiller, and Klaus Obermayer.

A Survey of State Representation Learning for Deep Reinforcement Learning Riedmiller, and Klaus Obermayer

Reference 17

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Observation 2619fb39-ead0-4c0b-8f64-469fe06d1997 · outbound

This paper cites Unsupervised Representation Learning in Deep Reinforcement Learning: A Review.

A Survey of State Representation Learning for Deep Reinforcement Learning Unsupervised Representation Learning in Deep Reinforcement Learning: A Review

Reference 18

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Observation 56feb069-faba-436e-8b84-adafa5f7a471 · outbound

This paper cites Barlowrl: Barlow twins for data-efficient reinforcement learning, 2023.

A Survey of State Representation Learning for Deep Reinforcement Learning Barlowrl: Barlow twins for data-efficient reinforcement learning, 2023

Reference 19

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Observation 2c7a5e28-6427-413e-8fa0-4eecf71701f8 · outbound

This paper cites Scalable methods for computing state similarity in deterministic markov decision processes.

A Survey of State Representation Learning for Deep Reinforcement Learning Scalable methods for computing state similarity in deterministic markov decision processes

Reference 20

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Observation ad3d8022-57be-4282-8bb6-a97501533644 · outbound

This paper cites MIC o: Improved representations via sampling-based state similarity for markov decision processes.

A Survey of State Representation Learning for Deep Reinforcement Learning MIC o: Improved representations via sampling-based state similarity for markov decision processes

Reference 21

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This paper cites Learning action representations for reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Learning action representations for reinforcement learning

Reference 22

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This paper cites Why do we need large batchsizes in contrastive learning? a gradient-bias perspective.

A Survey of State Representation Learning for Deep Reinforcement Learning Why do we need large batchsizes in contrastive learning? a gradient-bias perspective

Reference 23

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Observation e48246f5-0fa4-4c5d-97f8-e4df61955af3 · outbound

This paper cites Focus-then-decide: Segmentation-assisted reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Focus-then-decide: Segmentation-assisted reinforcement learning

Reference 24

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Observation dade7f15-f3f4-494a-ab8b-70f658e21596 · outbound

This paper cites Learning representations via a robust behavioral metric for deep reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Learning representations via a robust behavioral metric for deep reinforcement learning

Reference 25

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Observation e44909d6-4cad-49b3-b706-f5a7fc74aa5e · outbound

This paper cites State chrono representation for enhancing generalization in reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning State chrono representation for enhancing generalization in reinforcement learning

Reference 26

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This paper cites Vision-Language Models Provide Promptable Representations for Reinforcement Learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Vision-Language Models Provide Promptable Representations for Reinforcement Learning

Reference 27

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This paper cites Exploring simple siamese representation learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Exploring simple siamese representation learning

Reference 28

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This paper cites Mudalige, Katharina Muelling, and John M.

A Survey of State Representation Learning for Deep Reinforcement Learning Mudalige, Katharina Muelling, and John M

Reference 29

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This paper cites Provable benefit of multitask representation learning in reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Provable benefit of multitask representation learning in reinforcement learning

Reference 30

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This paper cites Improving generalisation for temporal difference learning: The successor representation.

A Survey of State Representation Learning for Deep Reinforcement Learning Improving generalisation for temporal difference learning: The successor representation

Reference 31

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This paper cites Integrating state representation learning into deep reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Integrating state representation learning into deep reinforcement learning

Reference 32

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This paper cites The Hidden Pitfalls of the Cosine Similarity Loss.

A Survey of State Representation Learning for Deep Reinforcement Learning The Hidden Pitfalls of the Cosine Similarity Loss

Reference 33

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This paper cites Provably efficient rl with rich observations via latent state decoding.

A Survey of State Representation Learning for Deep Reinforcement Learning Provably efficient rl with rich observations via latent state decoding

Reference 34

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This paper cites Adapting Auxiliary Losses Using Gradient Similarity.

A Survey of State Representation Learning for Deep Reinforcement Learning Adapting Auxiliary Losses Using Gradient Similarity

Reference 35

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A Survey of State Representation Learning for Deep Reinforcement Learning Multi-view disentanglement for reinforcement learning with multiple cameras

Reference 36

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A Survey of State Representation Learning for Deep Reinforcement Learning Hanna, and Stefano V Albrecht

Reference 37

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This paper cites Conditional mutual information for disentangled representations in reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Conditional mutual information for disentangled representations in reinforcement learning

Reference 38

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This paper cites Provable benefits of representational transfer in reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Provable benefits of representational transfer in reinforcement learning

Reference 39

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A Survey of State Representation Learning for Deep Reinforcement Learning Dribo: Robust deep reinforcement learning via multi-view information bottleneck

Reference 40

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A Survey of State Representation Learning for Deep Reinforcement Learning Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks

Reference 41

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This paper cites Hyperbolic Discounting and Learning over Multiple Horizons.

A Survey of State Representation Learning for Deep Reinforcement Learning Hyperbolic Discounting and Learning over Multiple Horizons

Reference 42

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This paper cites Metrics for Finite Markov Decision Processes.

A Survey of State Representation Learning for Deep Reinforcement Learning Metrics for Finite Markov Decision Processes

Reference 43

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A Survey of State Representation Learning for Deep Reinforcement Learning Self-supervised Learning of Image Embedding for Continuous Control

Reference 44

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This paper cites For sale: State-action representation learning for deep reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning For sale: State-action representation learning for deep reinforcement learning

Reference 45

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A Survey of State Representation Learning for Deep Reinforcement Learning Towards General-Purpose Model-Free Reinforcement Learning

Reference 46

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A Survey of State Representation Learning for Deep Reinforcement Learning Rankme: Assessing the downstream performance of pretrained self-supervised representations by their rank

Reference 47

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A Survey of State Representation Learning for Deep Reinforcement Learning Learning and Leveraging World Models in Visual Representation Learning

Reference 48

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A Survey of State Representation Learning for Deep Reinforcement Learning Unresolved cited work

Reference 49

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A Survey of State Representation Learning for Deep Reinforcement Learning Visualizing and understanding atari agents

Reference 50

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A Survey of State Representation Learning for Deep Reinforcement Learning Bootstrap your own latent-a new approach to self-supervised learning

Reference 51

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A Survey of State Representation Learning for Deep Reinforcement Learning Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning

Reference 52

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This paper cites Stabilizing deep q-learning with convnets and vision transformers under data augmentation.

A Survey of State Representation Learning for Deep Reinforcement Learning Stabilizing deep q-learning with convnets and vision transformers under data augmentation

Reference 53

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A Survey of State Representation Learning for Deep Reinforcement Learning Masked autoencoders are scalable vision learners

Reference 54

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A Survey of State Representation Learning for Deep Reinforcement Learning Rainbow: Combining improvements in deep reinforcement learning

Reference 55

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A Survey of State Representation Learning for Deep Reinforcement Learning Multi-task deep reinforcement learning with popart

Reference 56

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A Survey of State Representation Learning for Deep Reinforcement Learning Burgess, Xavier Glorot, Matthew M

Reference 57

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A Survey of State Representation Learning for Deep Reinforcement Learning Darla: Improving zero-shot transfer in reinforcement learning

Reference 58

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A Survey of State Representation Learning for Deep Reinforcement Learning Learning deep representations by mutual information estimation and maximization

Reference 59

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This paper cites Revisiting data augmentation in deep reinforcement learning, 2024.

A Survey of State Representation Learning for Deep Reinforcement Learning Revisiting data augmentation in deep reinforcement learning, 2024

Reference 60

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This paper cites Spectrum random masking for generalization in image-based reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Spectrum random masking for generalization in image-based reinforcement learning

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This paper cites Generalization in reinforcement learning with selective noise injection and information bottleneck.

A Survey of State Representation Learning for Deep Reinforcement Learning Generalization in reinforcement learning with selective noise injection and information bottleneck

Reference 62

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This paper cites Zero-shot reinforcement learning via function encoders.

A Survey of State Representation Learning for Deep Reinforcement Learning Zero-shot reinforcement learning via function encoders

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:37.449983Z

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This paper cites Offline multitask representation learning for reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Offline multitask representation learning for reinforcement learning

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This paper cites Principled offline rl in the presence of rich exogenous information.

A Survey of State Representation Learning for Deep Reinforcement Learning Principled offline rl in the presence of rich exogenous information

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This paper cites Representation learning in deep rl via discrete information bottleneck.

A Survey of State Representation Learning for Deep Reinforcement Learning Representation learning in deep rl via discrete information bottleneck

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:37.743091Z

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This paper cites Zero-shot reinforcement learning from low quality data.

A Survey of State Representation Learning for Deep Reinforcement Learning Zero-shot reinforcement learning from low quality data

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:37.839439Z

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This paper cites Contextual decision processes with low bellman rank are pac-learnable.

A Survey of State Representation Learning for Deep Reinforcement Learning Contextual decision processes with low bellman rank are pac-learnable

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This paper cites Information-Bottleneck-Based Behavior Representation Learning for Multi-agent Reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Information-Bottleneck-Based Behavior Representation Learning for Multi-agent Reinforcement learning

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:34:50.236797Z

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Observation e1d3cdb0-89c9-420a-b031-d3b7b0f09b42 · outbound

This paper cites PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations.

A Survey of State Representation Learning for Deep Reinforcement Learning PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:38.254561Z

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A Survey of State Representation Learning for Deep Reinforcement Learning Unresolved cited work

Reference 71

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This paper cites Scaling up multi-task robotic reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Scaling up multi-task robotic reinforcement learning

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:38.671178Z

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This paper cites Terminal prediction as an auxiliary task for deep reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Terminal prediction as an auxiliary task for deep reinforcement learning

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:38.806508Z

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This paper cites Towards Robust Bisimulation Metric Learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Towards Robust Bisimulation Metric Learning

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:34:49.900073Z

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Observation f0c82f2f-9e5e-49b2-833d-cb51c9ae672b · outbound

This paper cites A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning.

A Survey of State Representation Learning for Deep Reinforcement Learning A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:34:49.702870Z

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Observation 744b1512-e3c0-45ec-9d1e-50d5ebdc8aab · outbound

This paper cites Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:34:49.424737Z

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Observation 0dbccc72-5fb9-4044-918e-4a195eee8286 · outbound

This paper cites Auto-Encoding Variational Bayes.

A Survey of State Representation Learning for Deep Reinforcement Learning Auto-Encoding Variational Bayes

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:39.165844Z

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This paper cites Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels.

A Survey of State Representation Learning for Deep Reinforcement Learning Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels

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This paper cites Pac reinforcement learning with rich observations.

A Survey of State Representation Learning for Deep Reinforcement Learning Pac reinforcement learning with rich observations

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:39.274360Z

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This paper cites Guaranteed discovery of control-endogenous latent states with multi-step inverse models.

A Survey of State Representation Learning for Deep Reinforcement Learning Guaranteed discovery of control-endogenous latent states with multi-step inverse models

Reference 80

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This paper cites Reinforcement Learning with Augmented Data.

A Survey of State Representation Learning for Deep Reinforcement Learning Reinforcement Learning with Augmented Data

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:39.383806Z

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This paper cites Metrics and continuity in reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Metrics and continuity in reinforcement learning

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:39.433199Z

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This paper cites A path towards autonomous machine intelligence version 0.9.

A Survey of State Representation Learning for Deep Reinforcement Learning A path towards autonomous machine intelligence version 0.9

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:39.490486Z

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This paper cites Unsupervised state representation learning with robotic priors: a robustness benchmark.

A Survey of State Representation Learning for Deep Reinforcement Learning Unsupervised state representation learning with robotic priors: a robustness benchmark

Reference 85

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:34:49.177840Z

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Observation 453d13b6-58a2-45eb-89f8-95f7d3a24ff5 · outbound

This paper cites State Representation Learning for Control: An Overview.

A Survey of State Representation Learning for Deep Reinforcement Learning State Representation Learning for Control: An Overview

Reference 86

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:34:48.979376Z

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Observation e7d23b61-9307-4e5b-be45-8bcdc6ae0445 · outbound

This paper cites Normalization enhances generalization in visual reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Normalization enhances generalization in visual reinforcement learning

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:39.836538Z

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Observation c02c11b6-0b44-485c-ad2f-cbf3405d2689 · outbound

This paper cites Provable general function class representation learning in multitask bandits and mdp.

A Survey of State Representation Learning for Deep Reinforcement Learning Provable general function class representation learning in multitask bandits and mdp

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:39.891192Z

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Observation e7eb5e7d-1038-4773-8ba9-97e034c0e064 · outbound

This paper cites On The Effect of Auxiliary Tasks on Representation Dynamics.

A Survey of State Representation Learning for Deep Reinforcement Learning On The Effect of Auxiliary Tasks on Representation Dynamics

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:34:48.676098Z

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Observation 51bcdc9a-5394-4412-932f-b6e6ec3ea9ff · outbound

This paper cites A Comprehensive Survey of Data Augmentation in Visual Reinforcement Learning.

A Survey of State Representation Learning for Deep Reinforcement Learning A Comprehensive Survey of Data Augmentation in Visual Reinforcement Learning

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:40.091630Z

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Observation a91ebd6d-25b4-4462-894d-84d4a62889e3 · outbound

This paper cites Revisiting plasticity in visual reinforcement learning: Data, modules and training stages.

A Survey of State Representation Learning for Deep Reinforcement Learning Revisiting plasticity in visual reinforcement learning: Data, modules and training stages

Reference 91

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Observation 567422ef-5732-429e-abac-83880cf997ca · outbound

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

A Survey of State Representation Learning for Deep Reinforcement Learning VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:40.275191Z

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Observation 8fb15b68-72f8-48fa-9d00-88093d78969a · outbound

This paper cites Where are we in the search for an artificial visual cortex for embodied intelligence? Advances in Neural Information Processing Systems, 36: 0 655--677, 2023.

A Survey of State Representation Learning for Deep Reinforcement Learning Where are we in the search for an artificial visual cortex for embodied intelligence? Advances in Neural Information Processing Systems, 36: 0 655--677, 2023

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:40.386436Z

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This paper cites Deep reinforcement and infomax learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Deep reinforcement and infomax learning

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:40.542795Z

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Observation 934a1bf8-71fe-4c20-8892-6045ae85f9c7 · outbound

This paper cites Multi-horizon representations with hierarchical forward models for reinforcement learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Multi-horizon representations with hierarchical forward models for reinforcement learning

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:40.720190Z

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Observation 248ddb6e-8d6f-42f7-9245-1ea4c28fb5c0 · outbound

This paper cites Towards Principled Representation Learning from Videos for Reinforcement Learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Towards Principled Representation Learning from Videos for Reinforcement Learning

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:40.760414Z

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Observation 0f6b23f9-3eb1-4c57-9a74-015de97bc54f · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

A Survey of State Representation Learning for Deep Reinforcement Learning Playing Atari with Deep Reinforcement Learning

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:40.865066Z

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This paper cites Towards Interpretable Reinforcement Learning Using Attention Augmented Agents.

A Survey of State Representation Learning for Deep Reinforcement Learning Towards Interpretable Reinforcement Learning Using Attention Augmented Agents

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:34:48.339822Z

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Observation ea189003-f8f4-4171-ab06-f01a02fe996c · outbound

This paper cites R3m: A universal visual representation for robot manipulation, 2022.

A Survey of State Representation Learning for Deep Reinforcement Learning R3m: A universal visual representation for robot manipulation, 2022

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:34:41.037102Z

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This paper cites Bridging state and history representations: Understanding self-predictive rl, 2024.

A Survey of State Representation Learning for Deep Reinforcement Learning Bridging state and history representations: Understanding self-predictive rl, 2024

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This paper cites Foundation policies with H ilbert representations.

A Survey of State Representation Learning for Deep Reinforcement Learning Foundation policies with H ilbert representations

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Pith citing papers

Observation ed9024be-4180-4384-af60-c34f0e2c26fc · inbound

Interpret Policies in Deep Reinforcement Learning using SILVER with RL-Guided Labeling: A Model-level Approach to High-dimensional and Multi-action Environments cites this paper.

Interpret Policies in Deep Reinforcement Learning using SILVER with RL-Guided Labeling: A Model-level Approach to High-dimensional and Multi-action Environments A Survey of State Representation Learning for Deep Reinforcement Learning

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Belief-State RWKV for Reinforcement Learning under Partial Observability A Survey of State Representation Learning for Deep Reinforcement Learning

Reference 3

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Observation 1919587a-f114-488e-a6e2-c5f4923b6f99 · inbound

Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning cites this paper.

Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning A Survey of State Representation Learning for Deep Reinforcement Learning

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:16:26.328081Z

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Observation 6f8e3d58-0158-49b3-bc5a-a4fbcba1d4c5 · inbound

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Abstraction for Offline Goal-Conditioned Reinforcement Learning A Survey of State Representation Learning for Deep Reinforcement Learning

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Resolution: verified exact; arxiv_id, observed 2026-05-22T07:51:16.511799Z

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Observation b635bf3c-5141-4366-8881-ccae312cd0f5 · inbound

A Unified Causal-Origin Taxonomy of Distributional Shifts in Reinforcement Learning cites this paper.

A Unified Causal-Origin Taxonomy of Distributional Shifts in Reinforcement Learning A Survey of State Representation Learning for Deep Reinforcement Learning

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Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning A Survey of State Representation Learning for Deep Reinforcement Learning

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:59:40.696101Z

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Observation 88367737-f250-4c95-9ced-7c15ca0d2c37 · inbound

V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control cites this paper.

V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control A Survey of State Representation Learning for Deep Reinforcement Learning

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