Paper Citation Record · LEDGER

Attention Mechanism, Max-Affine Partition, and Universal Approximation

As of 16 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2504.19901.

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

pith.paper-citation-record.v1
2504.19901 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:49:39.652481Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

20 of 20 outbound references displayed

verified exact0
verified fuzzy2
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b507613a-4654-4f7a-a466-b54a2cea6533 · outbound

This paper cites GPT-4 Technical Report.

Attention Mechanism, Max-Affine Partition, and Universal Approximation GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.563435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2be047a2-6e9d-4a15-85fa-95bf7424e1e5 · outbound

This paper cites Superiority of softmax: Unveiling the performance edge over linear attention.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Superiority of softmax: Unveiling the performance edge over linear attention

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.592971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 239a4c30-fddb-4f79-a561-9d1bf322860a · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Attention Mechanism, Max-Affine Partition, and Universal Approximation BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.597272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a54420d-e062-4547-a14d-f7cd99503ed5 · outbound

This paper cites Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.606729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea2009c0-44ee-47e0-b72b-37f6bbe1b1bf · outbound

This paper cites On the Optimal Memorization Capacity of Transformers.

Attention Mechanism, Max-Affine Partition, and Universal Approximation On the Optimal Memorization Capacity of Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.611166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6f2e11b-9e34-421d-9f8c-524bb324f063 · outbound

This paper cites Transformers Provably Solve Parity Efficiently with Chain of Thought.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Transformers Provably Solve Parity Efficiently with Chain of Thought

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.615441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a1922f4-66b7-4a16-afdf-cf9a795ad73f · outbound

This paper cites Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.619918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bde8a35c-b449-439a-88ba-253bf7ebf5f2 · outbound

This paper cites In-context Learning and Induction Heads.

Attention Mechanism, Max-Affine Partition, and Universal Approximation In-context Learning and Induction Heads

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.629262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ba2cba4-d88c-45ee-9920-30b4ca025ece · outbound

This paper cites Transformers, parallel computation, and logarithmic depth.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Transformers, parallel computation, and logarithmic depth

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.633644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc945918-f96a-45da-8c6d-81d110d5c562 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Attention Mechanism, Max-Affine Partition, and Universal Approximation LLaMA: Open and Efficient Foundation Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.638354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bfb064f-9405-46f3-af0f-de6310a4f201 · outbound

This paper cites Are Transformers universal approximators of sequence-to-sequence functions?.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Are Transformers universal approximators of sequence-to-sequence functions?

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.647398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c4f421b-27cb-4979-82af-b5f27f6886f7 · outbound

This paper cites Provable Failure of Language Models in Learning Majority Boolean Logic via Gradient Descent.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Provable Failure of Language Models in Learning Majority Boolean Logic via Gradient Descent

Reference 1989

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.583561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6e7943d-c231-4bdf-bf24-8c190f154d70 · outbound

This paper cites Unified Training of Universal Time Series Forecasting Transformers.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Unified Training of Universal Time Series Forecasting Transformers

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.642809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31ee2ee9-d86a-424e-943c-ca46ec15186d · outbound

This paper cites DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome.

Attention Mechanism, Max-Affine Partition, and Universal Approximation DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.652481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c8e4ee2-65d2-4662-a941-dc4737d5bdc8 · outbound

This paper cites Construction of neural nets using the radon transform.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Construction of neural nets using the radon transform

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:49:40.028546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5fa68262-549b-45e8-9ad2-6af9e69e5ae0 · outbound

This paper cites The Llama 3 Herd of Models.

Attention Mechanism, Max-Affine Partition, and Universal Approximation The Llama 3 Herd of Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.602242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 289511ff-3ec4-438f-be27-4f0afc7f3bad · outbound

This paper cites Memorization Capacity of Multi-Head Attention in Transformers.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Memorization Capacity of Multi-Head Attention in Transformers

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.624488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6aae1c7-384d-41d5-b36d-978f6a39d766 · outbound

This paper cites Fundamental Limitations on Subquadratic Alternatives to Transformers.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Fundamental Limitations on Subquadratic Alternatives to Transformers

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.568945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 449140ae-de5b-49b3-b0e9-71b2f5e89f4e · outbound

This paper cites Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Gireeja Ranade Sastry, Amanda Askell, et al.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Gireeja Ranade Sastry, Amanda Askell, et al

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:49:40.047596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 26894e0e-f0a5-48e1-9329-2652a5012270 · outbound

This paper cites Provably learning a multi-head attention layer.

Attention Mechanism, Max-Affine Partition, and Universal Approximation Provably learning a multi-head attention layer

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-16T05:49:39.588423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.