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Paper Citation Record · LEDGER

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

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 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 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:07:52.248701Z

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

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

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.

source=arxiv_source observed=2026-08-09T18:07:52.248701Z digest=sha256:46865d0730076290c7e5393ba915e88e44b728a8df7fcd053ae102b46a6fa73a

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-23T03:27:41.641417Z digest=sha256:f2d22f1d963ecfa3b135b7861877bf43525c4147467e5b17a89fe363045c57fa

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:47:01.560107Z digest=sha256:13d7ea78d433c6e48ffd590c1221a8a5d4bb601c0988adf1a21930e428b13ac8

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.

source=arxiv_source observed=2026-08-07T06:03:49.520373Z digest=sha256:0976dd16274af42870bbca1f142d185e8c5162c748e898556bf5ddb8ff7c273d

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.

source=arxiv_source observed=2026-08-07T04:59:15.652640Z digest=sha256:97aa3d94073e419fc5f6b87e8bb3e6366381363e4383928ad3838f957e8e0115

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.

source=pdf_text observed=2026-08-06T18:15:47.730302Z digest=sha256:d83813bd48569573bddc5b931e0214069a00c5ae83bd0287f280f2a7ea39a192

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T20:46:15.275441Z digest=sha256:985f33ed03ee7180d464ab83273eb660d23d49d6a4f7e43d317383005f03e302

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:55:38.554161Z digest=sha256:dce7bb741493c6ddbd74d00347fcd89e470ff3628dc4e69585ad687af2829298

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-22T05:37:26.290308Z digest=sha256:49469931f3e1ed10eb89b787f774cc47874c62b571eb243d36c901af9d7cacc1

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T16:54:39.269896Z digest=sha256:adbc199d47a92d6215ed2c7895158703d3b66bc36e19e4eb06499003a5b6a8d1

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T19:27:25.233173Z digest=sha256:c846f4527a09025034c3df9ade5b8a089b545267c0bd32cf7ef02d83de2aaf8c

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T06:49:02.060472Z digest=sha256:d7838334a8cf846e4cd5bc30d7d6d5b563c3758418af0ad6fe79edd3c2ed6a3b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-25T19:12:22.513577Z digest=sha256:38b8065c8bf97c7d0c07c0e34a6ebe6556476d42bd73a12ac869da342ec32475

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T05:11:07.089829Z digest=sha256:93d80c798f944e62da474acdf63e5424a31d62f354728794c1608453ab4a9b17

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.

source=pdf_text observed=2026-07-12T12:05:57.682386Z digest=sha256:6dc3579116fb9c042576ffbabd0ba7d35ae1a819a4618007293610b4f56594ee