Paper Citation Record · LEDGER

Decoupling Search and Learning in Neural Net Training

As of 23 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2509.10973.

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

pith.paper-citation-record.v1
2509.10973 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:24:37.152466Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

17 of 17 outbound references displayed

verified exact0
verified fuzzy0
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6c7f4d26-7abb-4d22-ada6-aaefb4b5961f · outbound

This paper cites How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation.

Decoupling Search and Learning in Neural Net Training How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.067039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a93942d6-f68d-4fc3-b431-8c092ffd0a20 · outbound

This paper cites Towards scaling difference target propagation by learning backprop targets.

Decoupling Search and Learning in Neural Net Training Towards scaling difference target propagation by learning backprop targets

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.072622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e6cce75-508f-43c7-87d5-49e9ac480efc · outbound

This paper cites The Forward-Forward Algorithm: Some Preliminary Investigations.

Decoupling Search and Learning in Neural Net Training The Forward-Forward Algorithm: Some Preliminary Investigations

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.077364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d26b90e-2814-4bdd-a7b0-9e46ce12c5ee · outbound

This paper cites Difference target propagation.

Decoupling Search and Learning in Neural Net Training Difference target propagation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.082726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f245c35-24dd-44d5-afed-175096a20836 · outbound

This paper cites Random synaptic feedback weights support error backpropagation for deep learning.

Decoupling Search and Learning in Neural Net Training Random synaptic feedback weights support error backpropagation for deep learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.088030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5fac232-78fd-420c-b8c3-dc4e00369216 · outbound

This paper cites Searching latent program spaces.

Decoupling Search and Learning in Neural Net Training Searching latent program spaces

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.093074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e29f3be6-2bd5-4c3e-b1de-e572ce01dd9b · outbound

This paper cites Layer by layer: Uncovering hidden representations in language models.

Decoupling Search and Learning in Neural Net Training Layer by layer: Uncovering hidden representations in language models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.103842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cafbd4c1-b40d-4494-bd21-8dc49e2b5305 · outbound

This paper cites A formal theory of inductive inference.

Decoupling Search and Learning in Neural Net Training A formal theory of inductive inference

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.108657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5643160-06e3-482f-9648-f37dc0701e11 · outbound

This paper cites Stanley and Risto Miikkulainen.

Decoupling Search and Learning in Neural Net Training Stanley and Risto Miikkulainen

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.113427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f93231d-5f4a-478f-b6a8-8597215683e0 · outbound

This paper cites Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning.

Decoupling Search and Learning in Neural Net Training Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.118300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b5ea806-585c-4b27-b2f9-509ae80c0109 · outbound

This paper cites Learning to Synthesize Programs as Interpretable and Generalizable Policies.

Decoupling Search and Learning in Neural Net Training Learning to Synthesize Programs as Interpretable and Generalizable Policies

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.123163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4104c77d-ca62-4f6f-8045-d1768fa344e1 · outbound

This paper cites Neural network diffusion, 2024.

Decoupling Search and Learning in Neural Net Training Neural network diffusion, 2024

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.128930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a8708c4-5c9b-45fc-8881-2a49862ec5f6 · outbound

This paper cites Natural evolution strategies.

Decoupling Search and Learning in Neural Net Training Natural evolution strategies

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.133615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9e62b00-b293-4fb2-b357-ffbf9419acdf · outbound

This paper cites write newline.

Decoupling Search and Learning in Neural Net Training write newline

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.137792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdaae36b-ee28-4a3a-b290-b5bd8d97bba5 · outbound

This paper cites @esa (Ref.

Decoupling Search and Learning in Neural Net Training @esa (Ref

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.143095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90e0cccf-03e7-4493-9af4-fa222250c74d · outbound

This paper cites an unresolved cited work.

Decoupling Search and Learning in Neural Net Training Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.147902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0b6c1f8-d68d-46a0-a7a0-1766338a25a5 · outbound

This paper cites Evolution Strategies as a Scalable Alternative to Reinforcement Learning.

Decoupling Search and Learning in Neural Net Training Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T17:24:37.152466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.