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Paper Citation Record · LEDGER

Agent-centric learning: from external reward maximization to internal knowledge curation

As of 7 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2507.22255.

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

pith.paper-citation-record.v1
2507.22255 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:58:03.858544Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T01:01:50.627177Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

13 of 13 outbound references displayed

  • verified exact2
  • verified fuzzy2
  • unresolved8
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 5b0ca714-b3a4-435c-8d90-3f31dec0325a · outbound

This paper cites Vime: Variational information maximizing exploration.

Agent-centric learning: from external reward maximization to internal knowledge curation Vime: Variational information maximizing exploration

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:58:04.465815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T11:58:03.791506Z digest=sha256:9cf4ec3c12aef089cf0eb6d9e2b1bfa51808eb625fcd65fbf5b64afb47927fc2

Observation 5b989bf6-02ee-4f85-a0c9-88c4756acd0b · outbound

This paper cites Reward is not Necessary: How to Create a Modular & Compositional Self-Preserving Agent for Life-Long Learning.

Agent-centric learning: from external reward maximization to internal knowledge curation Reward is not Necessary: How to Create a Modular & Compositional Self-Preserving Agent for Life-Long Learning

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-06T11:58:04.084475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T11:58:03.826691Z digest=sha256:bccc1ddde46a2c4626eeecb32c3798dada7d5c45d357c3b8d6719cc720f7a828

Observation 8d887da1-45a7-49f7-8fba-14ee57546a7d · outbound

This paper cites 2404928121.

Agent-centric learning: from external reward maximization to internal knowledge curation 2404928121

Reference 12

Resolution
malformed identifier
no resolver link, observed 2026-08-06T11:58:03.847501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:58:03.847501Z digest=sha256:6f150ce1832cc7014b5c60e2616d326bbd8e0a4529925b0c366035430dbbcef6

Observation 011ca0c2-068e-4a00-9553-374bde89f386 · outbound

This paper cites Harmonizing Program Induction with Rate-Distortion Theory.

Agent-centric learning: from external reward maximization to internal knowledge curation Harmonizing Program Induction with Rate-Distortion Theory

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T11:58:03.858544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:58:03.858544Z digest=sha256:46f494e1bdab63496621f9718755cbe2016a9f2a7be21d24307ab6f9a954c306

Observation 8cc95a0c-d057-47ce-a2eb-35e1671b92af · outbound

This paper cites The information bottleneck method.

Agent-centric learning: from external reward maximization to internal knowledge curation The information bottleneck method

Reference 2009

Resolution
unresolved
no resolver link, observed 2026-08-06T11:58:03.838978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:58:03.838978Z digest=sha256:814bf15bc46d6fb1e0e73e0a1ac0bf05f980097441ebc6a2c8e8334e5954fc6c

Observation 1ded20d0-b198-4d26-b4e6-8149e6bf8e3a · outbound

This paper cites Intrinsically-Motivated Humans and Agents in Open-World Exploration.

Agent-centric learning: from external reward maximization to internal knowledge curation Intrinsically-Motivated Humans and Agents in Open-World Exploration

Reference 2015

Resolution
verified exact
local_arxiv, observed 2026-08-06T11:58:04.153194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T11:58:03.810178Z digest=sha256:a67ca5629cedd82515b966197512d39218962c4017ad7bb084702438da848807

Observation 15ef19a5-5124-472e-96d2-d4dc9c016684 · outbound

This paper cites Risks from Learned Optimization in Advanced Machine Learning Systems.

Agent-centric learning: from external reward maximization to internal knowledge curation Risks from Learned Optimization in Advanced Machine Learning Systems

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-06T11:58:03.796973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:58:03.796973Z digest=sha256:24b63d6e5a2890412daae76321a5891c3a0ee31069bbbfc349c1523207f0054a

Observation f4640899-baca-44ce-9efe-7dfc1f4c885c · outbound

This paper cites Meta-learning curiosity algorithms.

Agent-centric learning: from external reward maximization to internal knowledge curation Meta-learning curiosity algorithms

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-06T11:58:03.744415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:58:03.744415Z digest=sha256:abc83151bcc9125ad12a046de62bfe810ce507ac8993fab89e78bf6a583ea5b6

Observation aac8032d-eac0-490e-b598-7de5da93ff14 · outbound

This paper cites Three Dogmas of Reinforcement Learning.

Agent-centric learning: from external reward maximization to internal knowledge curation Three Dogmas of Reinforcement Learning

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-06T11:58:03.715479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:58:03.715479Z digest=sha256:6ebcb8ceff3bb768103c0ee32d72000280f6067f2d0d2fa9e5f590d36384dc5d

Observation 434a26f0-1083-433d-bfd8-94779226a9e4 · outbound

This paper cites Benchmarking the Spectrum of Agent Capabilities.

Agent-centric learning: from external reward maximization to internal knowledge curation Benchmarking the Spectrum of Agent Capabilities

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T11:58:03.781339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:58:03.781339Z digest=sha256:3f3804bd36fb2e94d8a9f8c5782036df4e41d1d32018e6311bf9f356f0464762

Observation 5ccfd4e5-7aed-4a7b-af9d-b6632ea15f44 · outbound

This paper cites Rethinking the Foundations for Continual Reinforcement Learning.

Agent-centric learning: from external reward maximization to internal knowledge curation Rethinking the Foundations for Continual Reinforcement Learning

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T11:58:03.757284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:58:03.757284Z digest=sha256:5963f9a2abef817b6fb98ea9cfbe250a5e1593f6a1a9eae1e114813a14b3ddbc

Observation bece8ab2-2b51-4d1f-9eab-3e12940b7cfd · outbound

This paper cites Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning.

Agent-centric learning: from external reward maximization to internal knowledge curation Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T11:58:03.731987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:58:03.731987Z digest=sha256:bf764c0b83f16793799e813d4c2d6dc8b604844759e5995cf7a5981bb079a9bd

Observation 1a860ca6-3523-4976-a136-75088502a16c · outbound

This paper cites What can ai learn from human exploration? intrinsically-motivated humans and agents in open-world exploration.

Agent-centric learning: from external reward maximization to internal knowledge curation What can ai learn from human exploration? intrinsically-motivated humans and agents in open-world exploration

Reference 2025

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:58:04.495760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T11:58:03.771127Z digest=sha256:f7f4003ca273d1a3ebb7ff67221677dc4c1baf01b959499cd6dda7c318dd5ffe

Pith citing papers

Observation 227be599-4166-4e83-8f0a-53d537622d1b · inbound

Effective Explanations Support Planning Under Uncertainty cites this paper.

Effective Explanations Support Planning Under Uncertainty Agent-centric learning: from external reward maximization to internal knowledge curation

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-12T01:06:13.931945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-12T01:01:50.627177Z digest=sha256:8e36b6e85e326bf52d8e87c5183d6915f1d2b8373cab6df299991e5531aaa4af