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Paper Citation Record · LEDGER

TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2407.16357.

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

pith.paper-citation-record.v1
2407.16357 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:47:31.915813Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T14:49:41.516586Z

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 f2cb7a8d-2af5-4edd-9fc4-cc32e8f63423 · inbound

PinFM: Foundation Model for User Activity Sequences at a Billion-scale Visual Discovery Platform cites this paper.

PinFM: Foundation Model for User Activity Sequences at a Billion-scale Visual Discovery Platform TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T16:47:31.915813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:47:31.915813Z digest=sha256:c2da9044e9cfec4f9a4e075aaee2ab6b9fe3728823f4d9bce3a0bb12a06a7694

Observation 3740cdb9-4c97-4c36-8f77-adfce6b46759 · inbound

Large Foundation Model for Ads Recommendation cites this paper.

Large Foundation Model for Ads Recommendation TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-05T18:30:13.383422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:30:13.383422Z digest=sha256:53eb2e75294b0dd1942a443e8c7e0aa24f2212bb09229c2219fabb51c0d30945

Observation 130a8b38-c5ab-4001-9195-f528c73c5396 · inbound

Deep Multiple Quantization Network on Long Behavior Sequence for Click-Through Rate Prediction cites this paper.

Deep Multiple Quantization Network on Long Behavior Sequence for Click-Through Rate Prediction TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-05T14:49:41.522069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T14:49:41.459469Z digest=sha256:01dd9e175e1876c2e73995bbf7dc02fb78f0801a4bffff5695e7c70feeb84f1d

Observation 5aac34fa-b097-4ce1-be9e-f6a259c4d5f1 · inbound

Prediction Is Not Memory: Dual-Timescale Gated Profile Writing for Persistent User Modeling cites this paper.

Prediction Is Not Memory: Dual-Timescale Gated Profile Writing for Persistent User Modeling TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-02T08:56:26.709634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T08:56:26.709634Z digest=sha256:18c80bba09f3e7079552c4f39380f80b733007d349bbecf3c96491c0ba040de7