Paper Citation Record · LEDGER

Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2211.12316.

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

pith.paper-citation-record.v1
2211.12316 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:07:53.612987Z

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

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

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

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 651f7b2d-6cce-49cd-a35d-cc05da07108b · inbound

When Do Neural Networks Learn World Models? cites this paper.

When Do Neural Networks Learn World Models? Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T22:12:49.957609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6633a81-6adb-4a95-8692-630994c2530b · inbound

Characterising the Inductive Biases of Neural Networks on Boolean Data cites this paper.

Characterising the Inductive Biases of Neural Networks on Boolean Data Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

Reference 694

Resolution: unresolved; no resolver link, observed 2026-08-07T12:49:01.145824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46ed9756-da9a-476d-ac07-8a82207db68e · inbound

In-Context Learning Strategies Emerge Rationally cites this paper.

In-Context Learning Strategies Emerge Rationally Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T19:07:53.612987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 965fb1f4-d8ca-4031-85a5-2afe35778a2c · inbound

Parity Requires Unified Input Dependence and Negative Eigenvalues in SSMs cites this paper.

Parity Requires Unified Input Dependence and Negative Eigenvalues in SSMs Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T22:16:07.996946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4523a6c-32ba-4b04-84e2-4824b425a212 · inbound

On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime cites this paper.

On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-16T17:23:09.981113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 303ec49c-3c8d-4385-b4fd-977844d79869 · inbound

The two clocks and the innovation window: When and how generative models learn rules cites this paper.

The two clocks and the innovation window: When and how generative models learn rules Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T03:16:18.027875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c6b6a374-4273-4960-83d6-64b97cb5b4ac · inbound

Looped Transformers with Layer Normalization Provably Learn the Power Method cites this paper.

Looped Transformers with Layer Normalization Provably Learn the Power Method Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:22:35.270714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bde0fb00-7a27-480e-a501-819d8dd0ca91 · inbound

Can Transformers Really Do It All? On the Compatibility of Inductive Biases Across Tasks cites this paper.

Can Transformers Really Do It All? On the Compatibility of Inductive Biases Across Tasks Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T17:31:45.867744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.