Paper Citation Record · LEDGER

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents

As of 7 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2507.01823.

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

pith.paper-citation-record.v1
2507.01823 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:47:20.742361Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

36 of 36 outbound references displayed

verified exact1
verified fuzzy21
unresolved14
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 04e8cbc0-f772-4358-9ce7-06de442aa9d1 · outbound

This paper cites Learning dexterous in-hand manipulation.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Learning dexterous in-hand manipulation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:23.473018Z

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Observation 9263eaca-20d5-46ab-8758-8c32302f40e5 · outbound

This paper cites Multitask learning.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Multitask learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:23.314129Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6c0e3251-fa33-452d-9d3b-12d0c98feaee · outbound

This paper cites Deep reinforce- ment learning in a handful of trials using probabilistic dynamics models.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Deep reinforce- ment learning in a handful of trials using probabilistic dynamics models

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:23.112922Z

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Observation d1468e31-2710-4527-8c86-414adf765016 · outbound

This paper cites Distilling policy distillation.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Distilling policy distillation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:22.951909Z

Source-reported events for the cited work

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Observation c1a1e3d9-3583-458f-8612-acbcbdb931ac · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Model-agnostic meta-learning for fast adaptation of deep networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:22.809935Z

Source-reported events for the cited work

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Observation bcaecc37-eca4-461b-a67f-6cf8a4848649 · outbound

This paper cites Model predictive control: Theory and practice—a survey.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Model predictive control: Theory and practice—a survey

Reference 6

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Source-reported events for the cited work

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Observation 21171bc0-8935-4a9a-b243-2dcc2542cc23 · outbound

This paper cites PWM: Policy Learning with Multi-Task World Models.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents PWM: Policy Learning with Multi-Task World Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:20.450908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc07b9b3-bef6-4e53-bf11-8ff2c6c5b35c · outbound

This paper cites A Survey of Quantization Methods for Efficient Neural Network Inference.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:20.455721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4157507-8807-432c-8c42-20a3d1227fad · outbound

This paper cites Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:22.640716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ae87c9e5-3cd4-492a-9409-56fc1ef5fa57 · outbound

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

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Dream to Control: Learning Behaviors by Latent Imagination

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:20.472806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32e106f6-2853-4358-a9fc-d2896720d3ec · outbound

This paper cites Mastering Diverse Domains through World Models.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Mastering Diverse Domains through World Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:20.479734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d40029d-22c3-4768-b5a5-d251ef5f00fa · outbound

This paper cites TD-MPC2: Scalable, Robust World Models for Continuous Control.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents TD-MPC2: Scalable, Robust World Models for Continuous Control

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:20.496984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d46e977-1dfb-4464-b064-fed8fd283b8e · outbound

This paper cites Temporal difference learning for model predictive control.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Temporal difference learning for model predictive control

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:22.469698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 27ba02f8-e9c5-41b7-944d-3c14db794a55 · outbound

This paper cites Distilling the knowledge in a neural network.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Distilling the knowledge in a neural network

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:22.322084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5348b85e-9f2b-4581-aa07-f682510f00ac · outbound

This paper cites When to trust your model: Model-based policy optimization.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents When to trust your model: Model-based policy optimization

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:22.089670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b8835014-03a8-4cfd-8a00-e47530bd3960 · outbound

This paper cites QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation

Reference 16

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Source-reported events for the cited work

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Observation 86f32bda-427f-4723-aa9e-e3279ec207e5 · outbound

This paper cites Model- ensemble trust-region policy optimization.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Model- ensemble trust-region policy optimization

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.912607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bb48e649-4b62-4f98-bddb-3164cd34d21a · outbound

This paper cites Knowledge transfer in model-based reinforcement learning agents for efficient multi-task learning, 2025.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Knowledge transfer in model-based reinforcement learning agents for efficient multi-task learning, 2025

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.821531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 730faa61-02d7-4fd2-ab3a-9bb662814a4e · outbound

This paper cites Multimodal reinforcement learning: A survey and taxonomy.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Multimodal reinforcement learning: A survey and taxonomy

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.759795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5a7ab240-a1a4-4a21-a017-898f96770a69 · outbound

This paper cites End-to-end training of deep visuomotor policies.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents End-to-end training of deep visuomotor policies

Reference 20

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Source-reported events for the cited work

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Observation c5a911dd-e79b-49be-a946-c364248cf997 · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:20.587023Z

Source-reported events for the cited work

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Observation 783c56b4-a279-4c40-83f3-f2bed757516c · outbound

This paper cites Mixed Precision Training.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Mixed Precision Training

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:20.593145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b6c0716-2fa1-4c1f-ad24-0ddef9e18747 · outbound

This paper cites Playing atari with deep reinforcement learning, 2013.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Playing atari with deep reinforcement learning, 2013

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:20.605112Z

Source-reported events for the cited work

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Observation cb37187b-bee5-4690-8fff-bb312802380e · outbound

This paper cites Human-level control through deep reinforcement learning.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Human-level control through deep reinforcement learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.635312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 36319905-9737-4917-b7e8-8be34e6a0463 · outbound

This paper cites Curriculum learning for reinforcement learning domains: A framework and survey.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Curriculum learning for reinforcement learning domains: A framework and survey

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.599873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6eb62eab-a102-4875-a46f-4e3602fb9356 · outbound

This paper cites Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:20.638681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3269a788-29a1-41cb-8b7d-4c914b02014d · outbound

This paper cites Policy Distillation.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Policy Distillation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:20.656768Z

Source-reported events for the cited work

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Observation 302f9915-3495-492a-aec4-3b3abd2e996b · outbound

This paper cites Deep q-learning with quantized neural networks.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Deep q-learning with quantized neural networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.558810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f2cf4044-61c7-444f-902d-c6a24dd9a4ac · outbound

This paper cites Decoupling Representation Learning from Reinforcement Learning.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Decoupling Representation Learning from Reinforcement Learning

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-06T20:47:20.863019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f97136bf-5aa8-4c47-b6d4-b021f26006f6 · outbound

This paper cites Learning to predict by the methods of temporal differences.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Learning to predict by the methods of temporal differences

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.516200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d15d1547-8fb8-4f92-982a-973fe84e01fb · outbound

This paper cites Policy gradient methods for reinforcement learning with function approximation.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Policy gradient methods for reinforcement learning with function approximation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.467837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3be07ffd-7cf5-420b-a070-3daf4ac3127c · outbound

This paper cites dm_control: Software and Tasks for Continuous Control.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents dm_control: Software and Tasks for Continuous Control

Reference 32

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Source-reported events for the cited work

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Observation 3ace5a2a-ea29-4d25-a4d0-dc9b791c8d92 · outbound

This paper cites Distral: Robust multitask reinforcement learning.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Distral: Robust multitask reinforcement learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.429968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 468cf8ab-d718-4d55-b6ae-ae543a14a9ec · outbound

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

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.402282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ee31bc2-f3f4-4faf-9008-9b8082672b42 · outbound

This paper cites Conservative q-learning for offline reinforcement learn- ing.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents Conservative q-learning for offline reinforcement learn- ing

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.372696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 382e6af6-99ca-431b-83f3-ecad44d038a3 · outbound

This paper cites A survey on multi-task learning.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents A survey on multi-task learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:21.338061Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

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