Paper Citation Record · LEDGER

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps

As of 20 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2412.12024.

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

pith.paper-citation-record.v1
2412.12024 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:26:11.806504Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

45 of 45 outbound references displayed

verified exact1
verified fuzzy32
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8a34893a-972e-49ed-9d87-7a6e1f8c3e81 · outbound

This paper cites On Evaluation of Embodied Navigation Agents.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps On Evaluation of Embodied Navigation Agents

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T14:26:11.515243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37f40904-8f92-4925-8201-2cc3589eff1f · outbound

This paper cites Hindsight experience replay.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Hindsight experience replay

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.848578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1399f2d9-bef7-421a-baa4-ef66db2627b1 · outbound

This paper cites an unresolved cited work.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:26:12.828509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2840e049-4d4c-434d-bfc4-c02632ce58bf · outbound

This paper cites DeepMind Lab.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps DeepMind Lab

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T14:26:11.538307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2ede029-9672-41d0-99cd-f3a6f1f08605 · outbound

This paper cites Teaching a machine to read maps with deep reinforcement learning.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Teaching a machine to read maps with deep reinforcement learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.808836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 438ea220-4b1d-43d6-abd7-351a51c1d2d2 · outbound

This paper cites Learning to explore using active neural SLAM.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Learning to explore using active neural SLAM

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.789664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3503bce1-4b4b-42c4-8341-7ed848cd21c7 · outbound

This paper cites Learning exploration policies for navigation.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Learning exploration policies for navigation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.771219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 69226ac9-c22d-4758-8e3f-e2dddc795145 · outbound

This paper cites Deep reinforcement learning in a handful of trials using probabilistic dynamics models.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Deep reinforcement learning in a handful of trials using probabilistic dynamics models

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.749995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 34f9c502-bbcd-4873-b498-27e743171498 · outbound

This paper cites Learning to act by predicting the future.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Learning to act by predicting the future

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.722815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bf48cf93-f12a-4ff1-bc5b-cdad54c70a98 · outbound

This paper cites Leibo, and Charles Blundell.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Leibo, and Charles Blundell

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.704156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 87061269-af07-475b-b1a4-abe6bcac7bdd · outbound

This paper cites Cognitive mapping and planning for visual navigation.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Cognitive mapping and planning for visual navigation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.686417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ff58a015-c0be-4ffb-b8d6-7491667e408a · outbound

This paper cites Hyper N etworks.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Hyper N etworks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.664407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3b298aaa-6af3-4925-94df-5937f298dbe2 · outbound

This paper cites Learning latent dynamics for planning from pixels.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Learning latent dynamics for planning from pixels

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.637385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6e0aabce-0bfa-4908-9b67-727c265b9a17 · outbound

This paper cites Distributed prioritized experience replay.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Distributed prioritized experience replay

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T14:26:11.607247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43e0d6f1-5ce1-4091-bd24-2e980e98e28f · outbound

This paper cites Equivariant single view pose prediction via induced and restriction representations.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Equivariant single view pose prediction via induced and restriction representations

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.601173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d127af4b-3037-4681-ba80-b34c06fceff5 · outbound

This paper cites Continual model-based reinforcement learning with hypernetworks.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Continual model-based reinforcement learning with hypernetworks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.584081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 32eaeb63-09e5-4a9f-8083-ee0b67f1d731 · outbound

This paper cites Reinforcement learning with unsupervised auxiliary tasks.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Reinforcement learning with unsupervised auxiliary tasks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.564145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ccf61a8d-6852-422f-8722-db5b755246d9 · outbound

This paper cites Open-vocabulary pick and place via patch-level semantic maps.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Open-vocabulary pick and place via patch-level semantic maps

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.541061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 75dabcc9-0f20-4037-af67-af0a258986f6 · outbound

This paper cites Differentiable algorithm networks for composable robot learning.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Differentiable algorithm networks for composable robot learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.521147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9d8f071b-d038-4e8a-afc6-c68b5abfaea0 · outbound

This paper cites Practice Makes Perfect: Planning to Learn Skill Parameter Policies.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Practice Makes Perfect: Planning to Learn Skill Parameter Policies

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T14:26:11.638162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3626f9c-bd10-4cde-9a81-d365b9b96a9f · outbound

This paper cites Playing FPS games with deep reinforcement learning.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Playing FPS games with deep reinforcement learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.499038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c2c349a4-631d-41e8-8b32-8e19787d5ca8 · outbound

This paper cites Gated path planning networks.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Gated path planning networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.479120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cc5755ab-9cd7-4531-afe2-d1a2e8b257d8 · outbound

This paper cites Discriminative particle filter reinforcement learning for complex partial observations.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Discriminative particle filter reinforcement learning for complex partial observations

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.459211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1a8f8d6a-f220-4ae3-8f9d-e030bb359b46 · outbound

This paper cites Ballard, Andrea Banino, Misha Denil, Ross Goroshin, Laurent Sifre, Koray Kavukcuoglu, Dharshan Kumaran, and Raia Hadsell.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Ballard, Andrea Banino, Misha Denil, Ross Goroshin, Laurent Sifre, Koray Kavukcuoglu, Dharshan Kumaran, and Raia Hadsell

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.439031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3415ef71-ff1a-454a-869b-633efb9ec312 · outbound

This paper cites Learning to navigate in cities without a map.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Learning to navigate in cities without a map

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.419319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation be39e87a-a8d1-4ced-aa6f-c1a4c35a3dd1 · outbound

This paper cites Rusu, Joel Veness, Marc G.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Rusu, Joel Veness, Marc G

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T14:26:11.683495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29ada361-5167-4f40-b9c2-1e71e65ab250 · outbound

This paper cites Goal-directed planning via hindsight experience replay.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Goal-directed planning via hindsight experience replay

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.389498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 046a6596-9c02-4743-a348-87a128a9e177 · outbound

This paper cites Value prediction network.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Value prediction network

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.366329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c2004631-5258-4bd2-b671-8787b9f454de · outbound

This paper cites Neural map: Structured memory for deep reinforcement learning.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Neural map: Structured memory for deep reinforcement learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.350271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c1d06af8-7d19-4c8c-a614-b51e67db3cbc · outbound

This paper cites Learning symmetric embeddings for equivariant world models.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Learning symmetric embeddings for equivariant world models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.333248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3d15cd90-487f-47f6-9193-3a01f7d979c7 · outbound

This paper cites Temporal difference models: Model-free deep RL for model-based control.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Temporal difference models: Model-free deep RL for model-based control

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.316089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c08d3712-b277-4374-a953-a9303a6868c2 · outbound

This paper cites Mastering A tari, G o, chess and shogi by planning with a learned model.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Mastering A tari, G o, chess and shogi by planning with a learned model

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.299750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3985cce0-a9dd-4e5d-bda9-c32aae34d5ac · outbound

This paper cites Value iteration networks.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Value iteration networks

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.281561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3065d424-fd52-4466-9053-b9c7762f3c86 · outbound

This paper cites Probabilistic Robotics.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Probabilistic Robotics

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.263847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 699f11c6-e66c-4a78-8e7e-e7f11b107710 · outbound

This paper cites Grewe, and Jo \ a o Sacramento.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Grewe, and Jo \ a o Sacramento

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.246884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c9736984-7b79-4b95-b0fc-484f79e7d318 · outbound

This paper cites Unsupervised Predictive Memory in a Goal-Directed Agent.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Unsupervised Predictive Memory in a Goal-Directed Agent

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T14:26:11.746939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 744a391c-3acd-4e8d-8064-79cd98e4d209 · outbound

This paper cites Clara De Paolis Kaluza, Linfeng Zhao, Lawson Wong, and Rose Yu.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Clara De Paolis Kaluza, Linfeng Zhao, Lawson Wong, and Rose Yu

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.225587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7009cce6-56a4-40f3-8cfc-00c7882966a4 · outbound

This paper cites Toward compositional generalization in object-oriented world modeling.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Toward compositional generalization in object-oriented world modeling

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.205209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 166b5969-b28e-4850-be21-c88d03121327 · outbound

This paper cites Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning?.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Can Euclidean Symmetry be Leveraged in Reinforcement Learning and Planning?

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-11T14:26:11.992130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cd333d17-bd74-4222-9a4a-b14e4ba12d31 · outbound

This paper cites an unresolved cited work.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:26:12.186633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 702d6fad-72e0-4770-8997-4a681c044dd0 · outbound

This paper cites an unresolved cited work.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:26:12.170023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation eafbd434-0d8d-4206-8a1c-6f2d1b15472e · outbound

This paper cites an unresolved cited work.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:26:12.149452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 509e9ecc-ef8a-470c-ab6a-cb61a02f90b6 · outbound

This paper cites an unresolved cited work.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps Unresolved cited work

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T14:26:11.794881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 327a4d24-d801-4881-b71c-128d8777ec25 · outbound

This paper cites RTFM : Generalising to new environment dynamics via reading.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps RTFM : Generalising to new environment dynamics via reading

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:26:12.129085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d1341910-5644-4c32-b259-a51f2c413708 · outbound

This paper cites write newline.

Learning to Navigate in Mazes with Novel Layouts using Abstract Top-down Maps write newline

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-11T14:26:11.806504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.