Paper Citation Record · LEDGER

VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:1910.08348.

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

pith.paper-citation-record.v1
1910.08348 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 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 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T06:07:19.781695Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T21:00:09.597328Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 91bc5a84-e4c5-48bf-ae2f-a0f621911dd7 · inbound

Hierarchical Meta-Reinforcement Learning via Automated Macro-Action Discovery cites this paper.

Hierarchical Meta-Reinforcement Learning via Automated Macro-Action Discovery VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T14:31:29.813274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a6641e8-aa33-4f53-8fdc-5647549e798e · inbound

To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization cites this paper.

To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-09T18:07:52.248701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b6f77e0-b8ec-45b2-a460-588ba5d7c324 · inbound

Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks cites this paper.

Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:32:28.770473Z

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.

Observation 0a639983-ad2c-4d88-b0bd-d292922863b0 · inbound

Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized Environments cites this paper.

Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized Environments VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-16T06:07:19.781695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91a1adaa-d2c2-4a48-b4ef-bfba33e0b3a5 · inbound

Unsupervised Meta-Testing with Conditional Neural Processes for Hybrid Meta-Reinforcement Learning cites this paper.

Unsupervised Meta-Testing with Conditional Neural Processes for Hybrid Meta-Reinforcement Learning VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T10:47:01.560107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4e594ae-0268-48e9-92cc-2d4f6d18b387 · inbound

Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens cites this paper.

Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T06:03:49.520373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4fa4b48-1ca3-430c-84bc-3d69928723fd · inbound

Uncertainty Prioritized Experience Replay cites this paper.

Uncertainty Prioritized Experience Replay VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-07T04:59:15.652640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24750245-12b6-422a-8776-d0a684856296 · inbound

Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning cites this paper.

Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T18:32:40.212901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2603762d-7459-40a6-8dc3-8993e2926b9a · inbound

Behavioral Exploration: Learning to Explore via In-Context Adaptation cites this paper.

Behavioral Exploration: Learning to Explore via In-Context Adaptation VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T18:15:47.730302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9e7e083-7a17-48c6-a939-29950eedd8a7 · inbound

Adaptive Policy Backbone via Shared Network cites this paper.

Adaptive Policy Backbone via Shared Network VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:59.768452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03613371-8546-430f-8bc4-1e7dc9c526e3 · inbound

Meta-Learning and Meta-Reinforcement Learning -- Tracing the Path towards DeepMind's Adaptive Agent cites this paper.

Meta-Learning and Meta-Reinforcement Learning -- Tracing the Path towards DeepMind's Adaptive Agent VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 206

Resolution: verified exact; arxiv_id, observed 2026-05-15T20:46:35.673822Z

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.

Observation 95413c26-36ac-459d-8db7-bbc3463b9eb4 · inbound

Why Does Agentic Safety Fail to Generalize Across Tasks? cites this paper.

Why Does Agentic Safety Fail to Generalize Across Tasks? VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 130

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:06:00.188027Z

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.

Observation 4613549f-3a41-4aeb-a48d-d69254225a60 · inbound

CoRMA: Contrastive RMA for Contact-Rich Meta-Adaptation cites this paper.

CoRMA: Contrastive RMA for Contact-Rich Meta-Adaptation VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-22T05:41:08.540389Z

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.

Observation e3b3b8ab-84a0-4410-b161-b662c94e3906 · inbound

CoRMA: Contrastive RMA for Contact-Rich Meta-Adaptation cites this paper.

CoRMA: Contrastive RMA for Contact-Rich Meta-Adaptation VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-06-30T16:54:57.879037Z

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.

Observation 98b8a2ff-b665-4aef-90f2-3756bb0a9fe9 · inbound

Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning cites this paper.

Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:32:34.964861Z

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.

Observation 97b8931a-367d-474c-889b-ccb1fe060d7c · inbound

Learning to Adapt: Representation-Based Reinforcement Learning for Multi-Task Skill Transfer cites this paper.

Learning to Adapt: Representation-Based Reinforcement Learning for Multi-Task Skill Transfer VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:58:33.267513Z

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.

Observation fc2f4e5f-a2a1-4557-8438-c0cb9c7aa726 · inbound

In-Context World Modeling for Robotic Control cites this paper.

In-Context World Modeling for Robotic Control VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-04T21:00:09.598899Z

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.

Observation fc4ca216-a81a-4d85-9e56-e1d1ac0c9fb6 · inbound

In-Context World Modeling for Robotic Control cites this paper.

In-Context World Modeling for Robotic Control VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:29:51.584813Z

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.

Observation 40ae2581-9fbb-4985-ba1e-cffcc7728cb5 · inbound

In-Context World Modeling for Robotic Control cites this paper.

In-Context World Modeling for Robotic Control VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-12T12:05:57.682386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.