Paper Citation Record · LEDGER

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence

As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2607.22748.

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

pith.paper-citation-record.v1
2607.22748 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T08:29:36.699879Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

22 of 22 outbound references displayed

verified exact0
verified fuzzy0
unresolved22
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5690f267-3c67-40fd-a0a5-da3310b28816 · outbound

This paper cites Neural reuse: A fundamental organizational principle of the brain.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Neural reuse: A fundamental organizational principle of the brain

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.038272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31bcc8bc-1c4e-4d5c-b8f1-782db8ef119e · outbound

This paper cites Relational inductive biases, deep learning, and graph networks.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Relational inductive biases, deep learning, and graph networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.093329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17294080-f8f2-4f15-8b72-507326ec0ff8 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.172397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9968e45e-75f9-4401-9578-ee0ae4a1d537 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence On the Opportunities and Risks of Foundation Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.225814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44e85dd7-89d0-4dd4-ad97-04cb45defaad · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing sys- tems, 33:1877–1901, 2020.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Language models are few-shot learners.Advances in neural information processing sys- tems, 33:1877–1901, 2020

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.301126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 804babca-75ae-4fb1-b640-a4f691e67c98 · outbound

This paper cites Parameter-efficient fine-tuning of large-scale pre-trained language models.Nature machine intelligence, 5(3):220–235, 2023.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Parameter-efficient fine-tuning of large-scale pre-trained language models.Nature machine intelligence, 5(3):220–235, 2023

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.360696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef286b1a-95f2-4967-9984-3847728802cb · outbound

This paper cites Neuroscience-inspired artificial intelligence.Neuron, 95(2):245–258, 2017.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Neuroscience-inspired artificial intelligence.Neuron, 95(2):245–258, 2017

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.415798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4cb1209-444d-4fd0-b5aa-901c7fa871ac · outbound

This paper cites Deep residual learning for image recognition.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Deep residual learning for image recognition

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.479073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11d0e2cb-f5f9-44e2-b5bc-1b0a31e45797 · outbound

This paper cites Experience-dependent structural synaptic plas- ticity in the mammalian brain.Nature Reviews Neuroscience, 10(9):647–658, 2009.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Experience-dependent structural synaptic plas- ticity in the mammalian brain.Nature Reviews Neuroscience, 10(9):647–658, 2009

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.534452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05bd98cf-cae3-4ee3-8013-785b27bfb185 · outbound

This paper cites Parameter- efficient transfer learning for nlp.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Parameter- efficient transfer learning for nlp

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.641781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4de70032-08df-4fa3-999b-d62b2ba189d9 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Lora: Low-rank adaptation of large language models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.712606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43b5a802-ca22-42d9-9061-fb20fb194bd5 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Semi-Supervised Classification with Graph Convolutional Networks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.765200Z

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Unavailable: canonical work link unavailable.

Observation f433d482-c8b5-4d0d-b145-ee8ded6f1db2 · outbound

This paper cites Deep learning.nature, 521(7553):436–444, 2015.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Deep learning.nature, 521(7553):436–444, 2015

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.846751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 563e401f-29c0-451d-827d-90561f72be09 · outbound

This paper cites Synaptic plasticity forms and functions.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Synaptic plasticity forms and functions

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:35.956698Z

Source-reported events for the cited work

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Observation ea8901e1-2614-4f70-acb8-2ba4cb3a0995 · outbound

This paper cites Cellular, synaptic and network effects of neuro- modulation.Neural Networks, 15(4-6):479–493, 2002.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Cellular, synaptic and network effects of neuro- modulation.Neural Networks, 15(4-6):479–493, 2002

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:36.015257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77455b1b-f621-4ff7-b187-ce16497a1c3d · outbound

This paper cites Human-level control through deep reinforcement learning.nature, 518(7540):529–533, 2015.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Human-level control through deep reinforcement learning.nature, 518(7540):529–533, 2015

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:36.096807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c8d124c-f107-443e-826a-651386e14efb · outbound

This paper cites Continual lifelong learning with neural networks: A review.Neural networks, 113:54–71, 2019.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Continual lifelong learning with neural networks: A review.Neural networks, 113:54–71, 2019

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:36.209906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 177728ac-af27-4248-ab42-ad8691f39ddd · outbound

This paper cites Modular Deep Learning.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Modular Deep Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:36.316848Z

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Unavailable: canonical work link unavailable.

Observation 3803fabb-3381-4070-a4bb-c95f0241108c · outbound

This paper cites A deep learning framework for neuroscience.Nature neuroscience, 22(11):1761–1770, 2019.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence A deep learning framework for neuroscience.Nature neuroscience, 22(11):1761–1770, 2019

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:36.464610Z

Source-reported events for the cited work

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Observation a4a4e044-eb33-4b6e-b815-72f3df1f4c7e · outbound

This paper cites Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:36.543882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ea366d9-1b01-4564-8606-fe7ad545bb76 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:36.624144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 720f2488-5494-451c-b971-8670caefe211 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T08:29:36.699879Z

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Pith citing papers

No inbound Pith citation observations are available.