Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On the Optimization and Generalization of Multi-head Attention
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.12680.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T04:39:55.010451Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T13:29:50.964232Z
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 5fbf6793-d710-4691-817d-2cdfbdbe287b · inbound
H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models cites this paper.
H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models On the Optimization and Generalization of Multi-head Attention
Reference 114
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T18:00:50.332170Z
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 a7bf4afd-cb6f-4825-8f2a-7f3396c30c9d · inbound
How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias cites this paper.
How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias On the Optimization and Generalization of Multi-head Attention
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T04:39:55.010451Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd45c953-249f-42de-9f57-f256a71e4bd0 · inbound
A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization cites this paper.
A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization On the Optimization and Generalization of Multi-head Attention
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T06:10:17.345237Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8270ac6b-bb71-4d17-acb4-c80c0289ccde · inbound
Structure Before Collapse: Transient semantic geometry in next-token prediction cites this paper.
Structure Before Collapse: Transient semantic geometry in next-token prediction On the Optimization and Generalization of Multi-head Attention
Reference 201
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T13:29:50.966010Z
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 e9cbbafc-1209-481a-8049-06b45c4e698f · inbound
Faster Query-Key Learning Sharpens Attention in Self-Attention Models cites this paper.
Faster Query-Key Learning Sharpens Attention in Self-Attention Models On the Optimization and Generalization of Multi-head Attention
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:39:18.066978Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.