Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-10T08:08:05.926366Z
Paper Citation Record · LEDGER
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note
As of 23 July 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2604.15739.
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 2026-07-23T06:31:01.910684+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
15 of 15 outbound references displayed
- verified exact8
- verified fuzzy7
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b36ed04c-ada0-4556-b986-0560a78d7613 · outbound
This paper cites OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T18:30:36.120082Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation bbf29471-3c79-4792-8aee-58ded66f62d0 · outbound
This paper cites How well does generative recommendation generalize?.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note How well does generative recommendation generalize?
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T09:08:26.715541Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation 11148858-c029-407e-bb69-30d93896aaa3 · outbound
This paper cites an unresolved cited work.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Unresolved cited work
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T11:25:03.783741Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation 1bc5f12c-c17b-49c1-81d3-74f588ed57e4 · outbound
This paper cites A Survey on Generative Recommendation: Data, Model, and Tasks.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note A Survey on Generative Recommendation: Data, Model, and Tasks
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T01:43:49.126345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation c8274038-be4c-4aa9-8481-eb2f33091b60 · outbound
This paper cites an unresolved cited work.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Unresolved cited work
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T11:25:03.773445Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation 2add0742-14ff-4739-b7be-2b1081b6062d · outbound
This paper cites an unresolved cited work.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Unresolved cited work
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T11:25:03.781190Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation d0e89c50-9b38-4030-994c-f83c82129539 · outbound
This paper cites InProceedings of the 2025 Conference on Empirical Methods in Natural Language Processing.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note InProceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T11:25:03.786664Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation b94266d5-28fb-4226-8488-626ed13c02dd · outbound
This paper cites an unresolved cited work.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Unresolved cited work
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T11:25:03.778647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation 5e32701c-45de-4b6d-b4c5-a2de4d22c383 · outbound
This paper cites an unresolved cited work.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Unresolved cited work
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T11:25:03.770893Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation 7896b1cd-dfaf-485e-952f-379aaec61809 · outbound
This paper cites an unresolved cited work.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Unresolved cited work
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T11:25:03.776135Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation f2701f6c-5b44-4e73-8aa0-4a764c8da4a1 · outbound
This paper cites an unresolved cited work.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Unresolved cited work
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:22:37.762016Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation 7218bd43-2a5b-46a1-a01c-25c2e932077b · outbound
This paper cites Dos: Dual-flow orthogonal semantic ids for recommendation in meituan.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Dos: Dual-flow orthogonal semantic ids for recommendation in meituan
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:22:37.759679Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation cb108e31-1ead-4844-9001-cdd3d7c22277 · outbound
This paper cites Gpr: Towards a generative pre-trained one-model paradigm for large-scale advertising recommendation.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Gpr: Towards a generative pre-trained one-model paradigm for large-scale advertising recommendation
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:22:37.754778Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation a6775f62-94e6-4a4a-9f4c-0368e464f75b · outbound
This paper cites Onemall: One model, more scenarios–end-to-end generative recommender family at kuaishou e-commerce.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Onemall: One model, more scenarios–end-to-end generative recommender family at kuaishou e-commerce
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T09:08:26.720266Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Observation c0f0d1c9-e25a-4bb7-8de7-a94f08f53b74 · outbound
This paper cites Farewell to item ids: Unlocking the scaling potential of large ranking models via semantic tokens.
On the Equivalence Between Auto-Regressive Next Token Prediction and Full-Item-Vocabulary Maximum Likelihood Estimation in Generative Recommendation--A Short Note Farewell to item ids: Unlocking the scaling potential of large ranking models via semantic tokens
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:22:37.751986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.
Pith citing papers
No inbound Pith citation observations are available.