Paper Citation Record · LEDGER

The Importance of Being Lazy: Scaling Limits of Continual Learning

As of 18 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 2 inbound Pith citation observations for arXiv:2506.16884.

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

pith.paper-citation-record.v1
2506.16884 v2

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:21:07.070864Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T22:34:25.245853Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T15:21:09.201567Z

Reference resolution

13 of 13 outbound references displayed

verified exact1
verified fuzzy3
unresolved6
parse uncertain0
malformed identifier2
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5113bd54-154c-439e-b9e2-a03149487c01 · outbound

This paper cites Lin, S., Ju, P., Liang, Y ., and Shroff, N.

The Importance of Being Lazy: Scaling Limits of Continual Learning Lin, S., Ju, P., Liang, Y ., and Shroff, N

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:21:07.177727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3ca92c22-0430-4671-bd18-13913867f075 · outbound

This paper cites An Empirical Study of $\mu$P Learning Rate Transfer.

The Importance of Being Lazy: Scaling Limits of Continual Learning An Empirical Study of $\mu$P Learning Rate Transfer

Reference 7

Resolution: malformed identifier; no resolver link, observed 2026-08-15T19:21:07.052422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b31939b-911c-4e01-b2b6-f9cd4754d9fb · outbound

This paper cites , identifying the respective terms in front of the relative γ0 expansion deriving from the other set of variables composing the self consistent system of equations.

The Importance of Being Lazy: Scaling Limits of Continual Learning , identifying the respective terms in front of the relative γ0 expansion deriving from the other set of variables composing the self consistent system of equations

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:21:07.169909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e6b93c76-a389-49dc-b312-5f958ab811c1 · outbound

This paper cites Our theory characterizes the effect of increasing the degree of feature learningon CF, starting from the lazy training setting – for which CF is already known.

The Importance of Being Lazy: Scaling Limits of Continual Learning Our theory characterizes the effect of increasing the degree of feature learningon CF, starting from the lazy training setting – for which CF is already known

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:21:07.161649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c7779a8a-aa06-4ef6-877a-74aad4286ab7 · outbound

This paper cites an unresolved cited work.

The Importance of Being Lazy: Scaling Limits of Continual Learning Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:21:07.153754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 63420781-4a2d-4c1c-894e-672a5fbd34cd · outbound

This paper cites an unresolved cited work.

The Importance of Being Lazy: Scaling Limits of Continual Learning Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:21:07.146258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2ef84a95-7f7a-4ef9-8f39-c417547f2c5e · outbound

This paper cites Continual Learning of Natural Language Processing Tasks: A Survey.

The Importance of Being Lazy: Scaling Limits of Continual Learning Continual Learning of Natural Language Processing Tasks: A Survey

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-15T19:21:07.040987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0deb3f4-6a25-4e61-926c-1a14449db964 · outbound

This paper cites Finite Depth and Width Corrections to the Neural Tangent Kernel.

The Importance of Being Lazy: Scaling Limits of Continual Learning Finite Depth and Width Corrections to the Neural Tangent Kernel

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-15T19:21:07.038127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12da9fad-fdc8-4854-b9b1-88d2160fccb4 · outbound

This paper cites Empirical Analysis of the Hessian of Over-Parametrized Neural Networks.

The Importance of Being Lazy: Scaling Limits of Continual Learning Empirical Analysis of the Hessian of Over-Parametrized Neural Networks

Reference 2022

Resolution: malformed identifier; no resolver link, observed 2026-08-15T19:21:07.059435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fb98cd8-5e8b-4c60-8ec3-bf9646044bb2 · outbound

This paper cites Learning Bayesian Sparse Networks with Full Experience Replay for Continual Learning.

The Importance of Being Lazy: Scaling Limits of Continual Learning Learning Bayesian Sparse Networks with Full Experience Replay for Continual Learning

Reference 2023

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T19:21:07.138626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 24f46ac8-26fa-414b-b745-db998af3ee0e · outbound

This paper cites GPT-4 Technical Report.

The Importance of Being Lazy: Scaling Limits of Continual Learning GPT-4 Technical Report

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T19:21:07.056311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31afdded-a899-4501-88bf-1b7a71cbbec1 · outbound

This paper cites an unresolved cited work.

The Importance of Being Lazy: Scaling Limits of Continual Learning Unresolved cited work

Reference 2535

Resolution: verified exact; doi, observed 2026-08-15T19:21:07.091795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7050311b-7c52-41cf-8637-7c4ee2d231a9 · outbound

This paper cites Deep Neural Networks as Gaussian Processes.

The Importance of Being Lazy: Scaling Limits of Continual Learning Deep Neural Networks as Gaussian Processes

Reference 3529

Resolution: unresolved; no resolver link, observed 2026-08-15T19:21:07.043801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 80b0324e-1638-47dd-9c6c-4b1523657c01 · inbound

ImageHD: Energy-Efficient On-Device Continual Learning of Visual Representations via Hyperdimensional Computing cites this paper.

ImageHD: Energy-Efficient On-Device Continual Learning of Visual Representations via Hyperdimensional Computing The Importance of Being Lazy: Scaling Limits of Continual Learning

Reference 23

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T22:39:14.520662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b8c86221-a398-4bcb-9d61-07a5e2687e46 · inbound

There Will Be a Scientific Theory of Deep Learning cites this paper.

There Will Be a Scientific Theory of Deep Learning The Importance of Being Lazy: Scaling Limits of Continual Learning

Reference 97

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:21:09.204815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.