Paper Citation Record · LEDGER

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration

As of 21 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2505.23865.

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

pith.paper-citation-record.v1
2505.23865 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:51:38.604930Z

measured 11 of 11 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

11 of 11 outbound references displayed

verified exact0
verified fuzzy11
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9d399527-a410-4626-b54a-d43eb98ccbfd · outbound

This paper cites Coordinated multi-robot exploration.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration Coordinated multi-robot exploration

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:40.995015Z

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 6e6260a7-750d-455a-8499-fd3d0ab604f3 · outbound

This paper cites Carbone, D.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration Carbone, D

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:40.840465Z

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 93c972e7-f3ea-4035-889c-7b9099c8b1ea · outbound

This paper cites Houthooft et al.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration Houthooft et al

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:40.680369Z

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 9909c974-4596-4712-9ccf-c4b708163f7e · outbound

This paper cites Mutual information-based distributed sensing and control for multi-agent systems.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration Mutual information-based distributed sensing and control for multi-agent systems

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:40.544994Z

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 039529ad-19fa-4bd6-a133-c8dcc9c13fca · outbound

This paper cites Liu et al.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration Liu et al

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:40.338261Z

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 1ad24486-11d4-4863-94f1-940caa9d59b2 · outbound

This paper cites In search of compositional multi-task deep architectures for infor- mation theoretic field exploration.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration In search of compositional multi-task deep architectures for infor- mation theoretic field exploration

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:40.178287Z

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 3afae836-22c6-4ea6-9439-3cafd69d7160 · outbound

This paper cites Informative path planning for active field mapping under localization uncertainty.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration Informative path planning for active field mapping under localization uncertainty

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:39.992514Z

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 14149d43-3ccf-412d-9cc9-f60761d583df · outbound

This paper cites Singh et al.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration Singh et al

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:39.787590Z

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 08c01ba2-fb4d-48ca-896c-0f583f9f9de0 · outbound

This paper cites Sukhija et al.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration Sukhija et al

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:39.539537Z

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 7478303c-0301-4827-b5e5-bc6434418ecd · outbound

This paper cites Thrun, W.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration Thrun, W

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:39.239292Z

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 9328b9cb-2d4a-4359-93f5-38ac9731b9a7 · outbound

This paper cites A review on vision-based path planning and navigation for agricultural robots.

Combining Deep Architectures for Information Gain estimation and Reinforcement Learning for multiagent field exploration A review on vision-based path planning and navigation for agricultural robots

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:38.953330Z

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.

Pith citing papers

No inbound Pith citation observations are available.