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Paper Citation Record · LEDGER

Generative Flow Networks for Personalized Multimedia Systems: A Case Study on Short Video Feeds

As of 9 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 0 inbound Pith citation observations for arXiv:2508.17166.

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

pith.paper-citation-record.v1
2508.17166 v1

Coverage vector

measured 8 of 8 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:01:08.046172Z

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

8 of 8 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cc67c608-758e-487b-9c13-5418830ae92b · outbound

This paper cites Reinforcing Code Generation: Improving Text-to-SQL with Execution-Based Learning.

Generative Flow Networks for Personalized Multimedia Systems: A Case Study on Short Video Feeds Reinforcing Code Generation: Improving Text-to-SQL with Execution-Based Learning

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T17:01:08.018025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:01:08.018025Z digest=sha256:de4f338d954dbffea117da0a9a93622d5c051566857acc28a195b1bea645036a

Observation 95f29556-b7ce-4988-b150-1786f96ab181 · outbound

This paper cites Sparks of Tabular Reasoning via Text2SQL Reinforcement Learning.

Generative Flow Networks for Personalized Multimedia Systems: A Case Study on Short Video Feeds Sparks of Tabular Reasoning via Text2SQL Reinforcement Learning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T17:01:08.031911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:01:08.031911Z digest=sha256:62e9ebe50f74b8c1bf5739817a32278f0820b75357ca545a1d8c5a06ffc19e3d

Observation db008dc5-86c1-462a-abe9-9eea22f2b14b · outbound

This paper cites In Findings of the Association for Computational Lin- guistics: ACL 2024, pages 10796–10816, Bangkok, Thailand.

Generative Flow Networks for Personalized Multimedia Systems: A Case Study on Short Video Feeds In Findings of the Association for Computational Lin- guistics: ACL 2024, pages 10796–10816, Bangkok, Thailand

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:01:08.232524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T17:01:08.037170Z digest=sha256:0190d94fd489620844d389ecd38f1d4001ccaa4a425f216dbdfa08f55c6d0601

Observation a7426894-14da-441b-87a8-70b0322ab50b · outbound

This paper cites arXiv preprint arXiv:2403.02951.

Generative Flow Networks for Personalized Multimedia Systems: A Case Study on Short Video Feeds arXiv preprint arXiv:2403.02951

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T17:01:08.041756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:01:08.041756Z digest=sha256:572e1798638215ac7969b049438118a4ae3fee9ad1b42ac474145ceea119d264

Observation a1bb4d08-f510-4e00-b75a-4f3df9de4ffa · outbound

This paper cites In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 3501–3532, Singapore.

Generative Flow Networks for Personalized Multimedia Systems: A Case Study on Short Video Feeds In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 3501–3532, Singapore

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:01:08.217501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T17:01:08.046172Z digest=sha256:19795385fbf059ca496fed9bc32a4771050eb1975c163122e8ade2c1b8e97225

Observation 6b751996-7d71-4cd8-85be-1ceeaebd52c7 · outbound

This paper cites In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Process- ing, pages 1601–1611, Singapore.

Generative Flow Networks for Personalized Multimedia Systems: A Case Study on Short Video Feeds In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Process- ing, pages 1601–1611, Singapore

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:01:08.263778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T17:01:08.022942Z digest=sha256:a4bb7de4306b4b581865852215df82c4d6d917e3d420ffa34b24817378b8e523

Observation 2def00f9-c10e-4313-a843-b5a81640ff8b · outbound

This paper cites In Pro- ceedings of the 2024 Conference on Empirical Meth- ods in Natural Language Processing, pages 22206– 22216, Miami, Florida, USA.

Generative Flow Networks for Personalized Multimedia Systems: A Case Study on Short Video Feeds In Pro- ceedings of the 2024 Conference on Empirical Meth- ods in Natural Language Processing, pages 22206– 22216, Miami, Florida, USA

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:01:08.247885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T17:01:08.027541Z digest=sha256:3e06e0f88cc4b055f565a1a9d8646cb52a444ffc4d6f45735fc40ab52099ef22

Observation 8759de6f-37e7-4002-af08-80f4e5578d7c · outbound

This paper cites LLM-Symbolic Integration for Robust Temporal Tabular Reasoning.

Generative Flow Networks for Personalized Multimedia Systems: A Case Study on Short Video Feeds LLM-Symbolic Integration for Robust Temporal Tabular Reasoning

Reference 2025

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T17:01:08.202046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T17:01:08.012199Z digest=sha256:79fd428d694e7e87cba5d71750633f085b5ff94f0873d8ab174c51f5a8ce9cbe

Pith citing papers

No inbound Pith citation observations are available.