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Paper Citation Record · LEDGER

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization

As of 21 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2507.19437.

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

pith.paper-citation-record.v1
2507.19437 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:02:17.856013Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

  • verified exact0
  • verified fuzzy5
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 70983f92-9837-4285-9b57-24a570670405 · outbound

This paper cites Deep Variational Information Bottleneck.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Deep Variational Information Bottleneck

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:02:17.776800Z digest=sha256:2b0423e89b2cabfa6fff1f69227c192f592b396bb272182f10384cc86e9fa20a

Observation ca3223a5-beeb-4180-8dda-abc423286f0d · outbound

This paper cites Continuous control with deep reinforcement learning.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Continuous control with deep reinforcement learning

Reference 9

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source=pdf_text observed=2026-08-15T18:02:17.814371Z digest=sha256:ec4ceddedc9352291644fd990bcfbb62f0837204025a74ecd5544bc32a84274a

Observation 337c7c55-a506-4949-8a30-2251b38d0264 · outbound

This paper cites Sim-to-real transfer of robotic control with dynamics randomization.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Sim-to-real transfer of robotic control with dynamics randomization

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7ce1a859-25ea-4ec6-9fe9-989d437334d8 · outbound

This paper cites A Study on Overfitting in Deep Reinforcement Learning.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization A Study on Overfitting in Deep Reinforcement Learning

Reference 18

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source=pdf_text observed=2026-08-15T18:02:17.856013Z digest=sha256:afb7539e6a93430ba680146b7a60044ace09128827155e5f0750ba0535d78213

Observation 0353aa20-0aa4-437d-92fa-4ef4ba5679a1 · outbound

This paper cites Auto-Encoding Variational Bayes.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Auto-Encoding Variational Bayes

Reference 1960

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source=pdf_text observed=2026-08-15T18:02:17.801493Z digest=sha256:d9fa3a450dedab88927bf8f08d624a8f70fe5f187bc34d5b207d3474bb2789b0

Observation 75f893ae-98ab-45cc-9aee-f33f7bc4fd67 · outbound

This paper cites Learning Vision-Guided Quadrupedal Locomotion End-to-End with Cross-Modal Transformers.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Learning Vision-Guided Quadrupedal Locomotion End-to-End with Cross-Modal Transformers

Reference 1968

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no resolver link, observed 2026-08-15T18:02:17.851337Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:02:17.851337Z digest=sha256:cbe12dcae6a42f7bd809dfa38995d4335d62d628547b981ae2a48874e1d9da42

Observation 51b43956-3996-4d02-bb88-fe14b3bf163e · outbound

This paper cites The information bottleneck method.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization The information bottleneck method

Reference 1998

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no resolver link, observed 2026-08-15T18:02:17.833618Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:02:17.833618Z digest=sha256:e6913c1af70b8018695b2005a2b5a15b5755ce2836447559d1bc8fdaccfc4eb2

Observation 469cfc6f-c533-490f-b09e-7271adb2bb4d · outbound

This paper cites Domain randomization for transferring deep neural networks from simulation to the real world.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Domain randomization for transferring deep neural networks from simulation to the real world

Reference 2000

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raw_fallback, observed 2026-08-15T18:02:18.190990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:02:17.837622Z digest=sha256:b3848914f899becfa61d34214e6421fa064411b002b198faa578a481db79b8d9

Observation 57c516bd-a80d-45d9-8220-24d4ac42eedb · outbound

This paper cites MINE: Mutual Information Neural Estimation.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization MINE: Mutual Information Neural Estimation

Reference 2004

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source=pdf_text observed=2026-08-15T18:02:17.782913Z digest=sha256:438d72e27e8978e2ff9969ffd98225f0f390f336551db01fce3e2806e056e1e9

Observation 4700c26e-fce6-4649-9050-e7a759815e06 · outbound

This paper cites Walter Murray Wonham.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Walter Murray Wonham

Reference 2012

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source=pdf_text observed=2026-08-15T18:02:17.845468Z digest=sha256:3d9fd66485beb2700df9a36423a58db052896cbb434641f91bf089e1d45098dd

Observation 8a236c2b-9353-4e7a-8d9b-eeb2ca39a87d · outbound

This paper cites Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

Reference 2013

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source=pdf_text observed=2026-08-15T18:02:17.810339Z digest=sha256:9b1747f195c62d999d977dcc069a59f1f320ec47eaf23e46cd8f4abacacdf936

Observation 10f9da3f-6aef-4d73-8cec-9d20d138b0a1 · outbound

This paper cites Generalization in reinforcement learning by soft data augmentation.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Generalization in reinforcement learning by soft data augmentation

Reference 2015

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:02:17.797215Z digest=sha256:a9fd68a64124e8d1e827b97ffb0f6dc0c042f647f9f2ee2ab36a4850c100e461

Observation 8f882d01-bb77-4c65-a797-3929d89177d4 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Representation Learning with Contrastive Predictive Coding

Reference 2016

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Observation 7cb4e739-3c7b-4829-93cb-c7ea4135be31 · outbound

This paper cites Mujoco: A physics engine for model-based control.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Mujoco: A physics engine for model-based control

Reference 2017

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation f26b0cc8-15e2-4f0b-8763-da5ace3fcdea · outbound

This paper cites Mastering Diverse Domains through World Models.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Mastering Diverse Domains through World Models

Reference 2018

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Observation 40ed379c-bcb4-430c-b503-d18c057b64e0 · outbound

This paper cites Eligibility traces for off-policy policy evaluation.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Eligibility traces for off-policy policy evaluation

Reference 2019

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T18:02:17.829040Z digest=sha256:84a56fe93e0536607826beccf5cf374f8bcedc3f663d4aed4777172a9fa175c7

Observation bb0af7d3-9f7f-4909-902d-9b27d3bacdf1 · outbound

This paper cites RMA: Rapid Motor Adaptation for Legged Robots.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization RMA: Rapid Motor Adaptation for Legged Robots

Reference 2020

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source=pdf_text observed=2026-08-15T18:02:17.805753Z digest=sha256:3e4e2edf3e5fd1e0a0944c8040f04be3663ae4b19b989e7f6279ea33980b0995

Observation 6ebcc287-be0f-44a4-ab75-e18fc9934948 · outbound

This paper cites Contextual Markov Decision Processes.

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization Contextual Markov Decision Processes

Reference 2023

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Pith citing papers

No inbound Pith citation observations are available.