Paper Citation Record · LEDGER

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation

As of 18 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:1908.06376.

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

pith.paper-citation-record.v1
1908.06376 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:51:25.820264Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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 fuzzy6
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 85853b39-2c9a-4d8d-a8f5-0cfe04b495e3 · outbound

This paper cites Deep Variational Information Bottleneck.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Deep Variational Information Bottleneck

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T12:51:25.730353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88117d59-ab7c-4152-a15d-a46e107a8f17 · outbound

This paper cites an unresolved cited work.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:51:26.098296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 04825327-e0f5-4944-b01c-1a87f8114bd0 · outbound

This paper cites The ﬁrst one is the state representation network with parameters F.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation The ﬁrst one is the state representation network with parameters F

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:51:26.028964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1a3ff7e7-4465-4f96-ac86-c9881bfeacde · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Playing Atari with Deep Reinforcement Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T12:51:25.774869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20309446-bb09-4f2c-8459-25c82163afed · outbound

This paper cites Transfer in RL has been evaluated on multiple similar tasks by Barreto et al.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Transfer in RL has been evaluated on multiple similar tasks by Barreto et al

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:51:26.080662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c57c572e-dedf-4a0d-96e5-d705fc3ee41b · outbound

This paper cites an unresolved cited work.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:51:26.063412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 81c2c2bf-d46f-49b2-b983-da42c8778541 · outbound

This paper cites [Borsa et al., 2018] work describes a USFA training method by adapting e-greedy Q learning for set of simple tasks in Deepmind-Lab [Beattie et al., 2016] simulator.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation [Borsa et al., 2018] work describes a USFA training method by adapting e-greedy Q learning for set of simple tasks in Deepmind-Lab [Beattie et al., 2016] simulator

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:51:26.046386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b406e7f5-89b3-402e-aa2a-05a4a1ce7743 · outbound

This paper cites Moreover, Alemi et al.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Moreover, Alemi et al

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:51:26.011392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3fec8220-fd49-4658-bf00-0e9156b036c9 · outbound

This paper cites Universal Successor Features Approximators.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Universal Successor Features Approximators

Reference 1991

Resolution: unresolved; no resolver link, observed 2026-08-14T12:51:25.742587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 192dd645-714a-4b2f-b1bc-bf2253bd8509 · outbound

This paper cites CrowdMove: Autonomous Mapless Navigation in Crowded Scenarios.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation CrowdMove: Autonomous Mapless Navigation in Crowded Scenarios

Reference 1993

Resolution: unresolved; no resolver link, observed 2026-08-14T12:51:25.747870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6836becf-4027-4d71-992a-7aa7fdfab20e · outbound

This paper cites Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow

Reference 1995

Resolution: unresolved; no resolver link, observed 2026-08-14T12:51:25.784760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 468a3a36-0182-4f46-bdbd-7a0a5052266a · outbound

This paper cites Auto-Encoding Variational Bayes.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Auto-Encoding Variational Bayes

Reference 2003

Resolution: unresolved; no resolver link, observed 2026-08-14T12:51:25.753912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed4cc222-9f72-4b08-a242-8c71609dade1 · outbound

This paper cites Deep learning and the information bottleneck principle.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Deep learning and the information bottleneck principle

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:51:26.115110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 004cd057-1325-4ba0-ab44-658b0645589f · outbound

This paper cites AI2-THOR: An Interactive 3D Environment for Visual AI.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation AI2-THOR: An Interactive 3D Environment for Visual AI

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-14T12:51:25.759225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc88868a-7f66-4858-9612-67b9550a39ab · outbound

This paper cites Asynchronous methods for deep reinforcement learning.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Asynchronous methods for deep reinforcement learning

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:51:26.132236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 609da4df-8f92-4ecb-a7a7-742fb1610f90 · outbound

This paper cites Universal Successor Representations for Transfer Reinforcement Learning.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Universal Successor Representations for Transfer Reinforcement Learning

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-14T12:51:25.769961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8ee7390-884f-4666-9c90-0027e8f2fa9e · outbound

This paper cites Deep Successor Reinforcement Learning.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation Deep Successor Reinforcement Learning

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-14T12:51:25.764844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 669a9079-086c-4a78-b01e-36f094357715 · outbound

This paper cites DeepMind Lab.

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation DeepMind Lab

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-14T12:51:25.736834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.