Paper Citation Record · LEDGER

ReZero is All You Need: Fast Convergence at Large Depth

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2003.04887.

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

pith.paper-citation-record.v1
2003.04887 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:33:13.537223Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T05:29:36.294672Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 82a7c88a-5694-4cd3-a124-441be8a2f3df · inbound

Optimizing Job Allocation using Reinforcement Learning with Graph Neural Networks cites this paper.

Optimizing Job Allocation using Reinforcement Learning with Graph Neural Networks ReZero is All You Need: Fast Convergence at Large Depth

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T21:33:13.537223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 143a60d4-5f6e-4944-bb99-00be61621381 · inbound

Residual Matrix Transformers: Scaling the Size of the Residual Stream cites this paper.

Residual Matrix Transformers: Scaling the Size of the Residual Stream ReZero is All You Need: Fast Convergence at Large Depth

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T22:10:38.027642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17fed5c3-6111-4af5-9a55-337f6767ef5a · inbound

NRR-Core: Non-Resolution Reasoning as a Computational Framework for Contextual Identity and Ambiguity Preservation cites this paper.

NRR-Core: Non-Resolution Reasoning as a Computational Framework for Contextual Identity and Ambiguity Preservation ReZero is All You Need: Fast Convergence at Large Depth

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T16:29:59.581831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d98b7031-33a1-441e-a186-0d56135e4b28 · inbound

Gated Normalization Removal and Scale Anchoring in Pre-Norm Transformers cites this paper.

Gated Normalization Removal and Scale Anchoring in Pre-Norm Transformers ReZero is All You Need: Fast Convergence at Large Depth

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-21T14:20:13.488924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 15f46023-078f-4a3e-ae84-15d5872d299b · inbound

Prototype Transformer: Towards Language Model Architectures Interpretable by Design cites this paper.

Prototype Transformer: Towards Language Model Architectures Interpretable by Design ReZero is All You Need: Fast Convergence at Large Depth

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-03T00:02:44.101431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6192be48-d836-4a44-82bd-1269e536e205 · inbound

Attention Residuals cites this paper.

Attention Residuals ReZero is All You Need: Fast Convergence at Large Depth

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:39:04.417303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 11dbc6f7-5f64-4677-b7d4-1d93de4fc0e6 · inbound

Deep learning-based phase-field modelling of brittle fracture in anisotropic media cites this paper.

Deep learning-based phase-field modelling of brittle fracture in anisotropic media ReZero is All You Need: Fast Convergence at Large Depth

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T07:15:11.922283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d6019ac9-1149-4c79-b6e1-d1f858ad7976 · inbound

PermaFrost-Attack: Stealth Pretraining Seeding(SPS) for planting Logic Landmines During LLM Training cites this paper.

PermaFrost-Attack: Stealth Pretraining Seeding(SPS) for planting Logic Landmines During LLM Training ReZero is All You Need: Fast Convergence at Large Depth

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T14:31:06.106897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0b98db03-3ca8-4038-b7e9-da68f3ff14d7 · inbound

TFM-Retouche: A Lightweight Input-Space Adapter for Tabular Foundation Models cites this paper.

TFM-Retouche: A Lightweight Input-Space Adapter for Tabular Foundation Models ReZero is All You Need: Fast Convergence at Large Depth

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:46:08.399364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1ba576e8-ae13-4c94-a357-c2a565748301 · inbound

TFM-Retouche: A Lightweight Input-Space Adapter for Tabular Foundation Models cites this paper.

TFM-Retouche: A Lightweight Input-Space Adapter for Tabular Foundation Models ReZero is All You Need: Fast Convergence at Large Depth

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:56:32.862307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 35cb177b-fd28-487a-88ab-9214f1376a2d · inbound

HAARES Half-Split Residual Basis Routing for Deep Transformers cites this paper.

HAARES Half-Split Residual Basis Routing for Deep Transformers ReZero is All You Need: Fast Convergence at Large Depth

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:55.423750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6b1937c2-340f-4e11-b0df-beac09ce8a8e · inbound

NNNN: Neural Networks for Newtonian Noise Mitigation at the Einstein Telescope cites this paper.

NNNN: Neural Networks for Newtonian Noise Mitigation at the Einstein Telescope ReZero is All You Need: Fast Convergence at Large Depth

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-04T05:29:36.296004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e60a34a5-6502-4401-b787-593681d9356c · inbound

Review Residuals: Update-Conditioned Residual Gating for Transformers cites this paper.

Review Residuals: Update-Conditioned Residual Gating for Transformers ReZero is All You Need: Fast Convergence at Large Depth

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-01T06:45:29.825910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b5d16741-b820-49e2-864e-22212dab0d7a · inbound

Learning in Curved Weight Space:Exponential-Linear Weight Reparameterization for Improved Optimization cites this paper.

Learning in Curved Weight Space:Exponential-Linear Weight Reparameterization for Improved Optimization ReZero is All You Need: Fast Convergence at Large Depth

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-14T14:15:46.074413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01d8864c-cdfd-4dec-90aa-8aed6ec39fdc · inbound

A Controlled Study of Attention-Only Transformers cites this paper.

A Controlled Study of Attention-Only Transformers ReZero is All You Need: Fast Convergence at Large Depth

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T16:19:08.119127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.