Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
VQL: An End-to-End Context-Aware Vector Quantization Attention for Ultra-Long User Behavior Modeling
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2508.17125.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T15:42:21.765330Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T07:01:01.442898Z
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 a2ea41d9-bc70-4c41-a0ad-e20867980842 · inbound
IAT: Instance-As-Token Compression for Historical User Sequence Modeling in Industrial Recommender Systems cites this paper.
IAT: Instance-As-Token Compression for Historical User Sequence Modeling in Industrial Recommender Systems VQL: An End-to-End Context-Aware Vector Quantization Attention for Ultra-Long User Behavior Modeling
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:01:01.454135Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 553a08a8-bbe5-46dc-94ca-b32e585ac4d4 · inbound
Teacher Retains Full Tokens, Student Merges Efficiently: TM20K for E-Commerce Sequence Modeling in Ad Recommendation cites this paper.
Teacher Retains Full Tokens, Student Merges Efficiently: TM20K for E-Commerce Sequence Modeling in Ad Recommendation VQL: An End-to-End Context-Aware Vector Quantization Attention for Ultra-Long User Behavior Modeling
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:42:21.765330Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.