Paper Citation Record · LEDGER

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning

As of 12 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2412.05766.

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

pith.paper-citation-record.v1
2412.05766 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:28:45.048339Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

17 of 17 outbound references displayed

verified exact1
verified fuzzy1
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ab188922-f77c-4f5a-8f2f-f8dc800750f9 · outbound

This paper cites Mastering Diverse Domains through World Models.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Mastering Diverse Domains through World Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:44.751929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5bb4fef-e4fd-4adb-9c5a-d3ea6286e56a · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning SAM 2: Segment Anything in Images and Videos

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:44.966115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45205631-176d-4256-855a-1bd18381dd90 · outbound

This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:45.002755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56254eb0-3883-49a8-b4d8-1c3d967b23c7 · outbound

This paper cites SmoothGrad: removing noise by adding noise.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning SmoothGrad: removing noise by adding noise

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:45.014569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 498ee4d0-47ef-408b-9e8d-d0e330dd76de · outbound

This paper cites DeepMind Control Suite.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning DeepMind Control Suite

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:45.020457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ff31b1c-18ba-41e2-b8ec-0e65e87809cb · outbound

This paper cites Denoised MDPs: Learning World Models Better Than the World Itself.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Denoised MDPs: Learning World Models Better Than the World Itself

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:45.031618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc6f1f18-a822-4c37-9fb2-dfb8ef8a9fe7 · outbound

This paper cites Generalizable Visual Reinforcement Learning with Segment Anything Model.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Generalizable Visual Reinforcement Learning with Segment Anything Model

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:45.037385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 854ae04f-e2d5-41b4-bfda-c1f862c70040 · outbound

This paper cites Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:45.043226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04ca557f-b8f5-4957-afbf-ef63cf70af38 · outbound

This paper cites We believe this level of resource consumption could be easily reduced.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning We believe this level of resource consumption could be easily reduced

Reference 300

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:28:45.494190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4c35734f-9b59-49d9-a1d7-97b26f67b1fe · outbound

This paper cites The Kinetics Human Action Video Dataset.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning The Kinetics Human Action Video Dataset

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:44.782737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f380f59-b967-4b6a-8c56-593ca4dcc279 · outbound

This paper cites Dream to Control: Learning Behaviors by Latent Imagination.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Dream to Control: Learning Behaviors by Latent Imagination

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:44.611761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad2e0e10-0ff0-4c11-95fa-176a9f6e83a4 · outbound

This paper cites Mastering Atari with Discrete World Models.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Mastering Atari with Discrete World Models

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:44.688087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aab0590e-5cf6-4c1c-ac04-b71506a2d545 · outbound

This paper cites Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:44.570722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e2ad742-594b-4923-884e-58e8215b2672 · outbound

This paper cites Model-Based Reinforcement Learning for Atari.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Model-Based Reinforcement Learning for Atari

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:44.771468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e832b5b3-2826-4730-99f8-90621918d39e · outbound

This paper cites Objective Mismatch in Model-based Reinforcement Learning.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Objective Mismatch in Model-based Reinforcement Learning

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:44.869965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a77ee94-2d1a-4ced-a14a-ed4b329fc617 · outbound

This paper cites Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T20:28:44.788015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 113827e4-2831-4d5e-9a97-95cfe4326c81 · outbound

This paper cites Value Gradient weighted Model-Based Reinforcement Learning.

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning Value Gradient weighted Model-Based Reinforcement Learning

Reference 2024

Resolution: verified exact; local_arxiv, observed 2026-08-11T20:28:45.221413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.