Paper Citation Record · LEDGER

EGA-V2: An End-to-end Generative Framework for Industrial Advertising

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2505.17549.

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

pith.paper-citation-record.v1
2505.17549 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:42:54.716645Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:38:39.864363Z

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 5e015e8a-55b8-4ab8-b944-55faa42d7e16 · inbound

FORGE: Forming Semantic Identifiers for Generative Retrieval in Industrial Datasets cites this paper.

FORGE: Forming Semantic Identifiers for Generative Retrieval in Industrial Datasets EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T15:17:07.630714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd141ec5-4525-40c1-8f68-035cb4072e24 · inbound

A Survey on Generative Recommendation: Data, Model, and Tasks cites this paper.

A Survey on Generative Recommendation: Data, Model, and Tasks EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 243

Resolution: verified exact; arxiv_id, observed 2026-05-18T03:50:52.002068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation be13a497-98ee-4667-b261-e7f02aef80a0 · inbound

Coarse-to-Fine Long-term Interest Modeling for Generative Recommendation cites this paper.

Coarse-to-Fine Long-term Interest Modeling for Generative Recommendation EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T04:15:19.267397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5797d188-4888-4f24-99be-b63c48a8a932 · inbound

MBGR: Multi-Business Prediction for Generative Recommendation at Meituan cites this paper.

MBGR: Multi-Business Prediction for Generative Recommendation at Meituan EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-13T19:18:09.337127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ebf1af00-83a0-4fb8-9f40-5ea8d55ed798 · inbound

Noise is not always detrimental: the capacity of quantum batteries is enhanced in black holes cites this paper.

Noise is not always detrimental: the capacity of quantum batteries is enhanced in black holes EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 62

Resolution: unresolved; no resolver link, observed 2026-07-13T09:29:29.046109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aad69cc4-5a8b-4a63-8414-83e2888b43ec · inbound

Semantic Trimming and Auxiliary Multi-step Prediction for Generative Recommendation cites this paper.

Semantic Trimming and Auxiliary Multi-step Prediction for Generative Recommendation EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:30:50.740247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 96513730-d4cd-4f5e-8b48-26f8bd18667f · inbound

UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent cites this paper.

UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:16:26.066424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation eb3fb5d3-a964-4c5e-8438-d2fbdfe95463 · inbound

UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent cites this paper.

UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T14:47:56.180060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 577a0d93-0204-4b07-aa9d-b7287dfae108 · inbound

SSRLive: Live Streaming Recommendation with Dynamic Semantic ID cites this paper.

SSRLive: Live Streaming Recommendation with Dynamic Semantic ID EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-02T20:07:21.853827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5f0eddd5-c323-4276-ad25-eb20b189e539 · inbound

OneRetrieval: Unifying Multi-Branch E-commerce Retrieval with an Editable Generative Model cites this paper.

OneRetrieval: Unifying Multi-Branch E-commerce Retrieval with an Editable Generative Model EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-07-03T16:38:39.866936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ec4def13-b6b3-4c6a-b438-dabb54c9342e · inbound

HGenPush: A Heterogeneous Generative Recommendation Architecture for Industrial Push Notification Systems cites this paper.

HGenPush: A Heterogeneous Generative Recommendation Architecture for Industrial Push Notification Systems EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-12T03:01:20.649010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 211d3016-cc96-4d13-a0cb-68cabca31229 · inbound

TSGR: Taobao Search Generative Retrieval cites this paper.

TSGR: Taobao Search Generative Retrieval EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T14:25:22.326604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f50da04a-5fe5-4bf1-8ea4-ba391b8517da · inbound

UniGD: A Unified Generative-Discriminative Framework for Industrial Retrieval cites this paper.

UniGD: A Unified Generative-Discriminative Framework for Industrial Retrieval EGA-V2: An End-to-end Generative Framework for Industrial Advertising

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T00:42:54.716645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.