Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.06567.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T00:38:48.844998Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T22:36:17.259517Z
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 7c3ec9b0-19d3-44b4-9da1-a7138d508484 · inbound
A Survey on Large Language Model Acceleration based on KV Cache Management cites this paper.
A Survey on Large Language Model Acceleration based on KV Cache Management DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion
Reference 213
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T00:38:48.844998Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3067072-352b-47bb-8ca1-7faa285b5a07 · inbound
Align Attention Heads Before Merging Them: An Effective Way for Converting MHA to GQA cites this paper.
Align Attention Heads Before Merging Them: An Effective Way for Converting MHA to GQA DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion
Reference 2013
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:19:22.990805Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd86d25f-ea9c-4a62-be9f-27dc4c157145 · inbound
Do Transformers Need Three Projections? Systematic Study of QKV Variants cites this paper.
Do Transformers Need Three Projections? Systematic Study of QKV Variants DHA: Learning Decoupled-Head Attention from Transformer Checkpoints via Adaptive Heads Fusion
Reference 68
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T22:36:17.261031Z
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.