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Paper Citation Record · LEDGER

Generative Optimization for Incentivized Advertising with Global Level Constraints

As of 7 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2608.04421.

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

pith.paper-citation-record.v1
2608.04421 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:25:19.545945Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

56 of 56 outbound references displayed

  • verified exact4
  • verified fuzzy1
  • unresolved51
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 89c205aa-534d-40a0-abc0-544ab30f9b3e · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 1

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Observation 2a3c6621-71d1-4da9-b90e-d032b251c48d · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 2

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Observation 01732180-46af-4ea2-b97d-91e826480703 · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Generative Optimization for Incentivized Advertising with Global Level Constraints An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 3

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Observation 4b1ff886-4eda-4b3b-a754-0b3183882bf7 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-07T00:25:18.837041Z digest=sha256:ec2a05dffad7d30b1ba64342f376ad42f6575eac392ab61cc9cf9e950176bfea

Observation 7ae02476-4647-4655-a590-1d581dfb4818 · outbound

This paper cites BCRLSP: An Offline Reinforcement Learning Framework for Sequential Targeted Promotion.

Generative Optimization for Incentivized Advertising with Global Level Constraints BCRLSP: An Offline Reinforcement Learning Framework for Sequential Targeted Promotion

Reference 5

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 1d85cc97-690b-4f92-b0a6-710d75a1a4b1 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 6

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Observation 52515b9c-a533-463d-a7a5-065b67f58d0f · outbound

This paper cites OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment.

Generative Optimization for Incentivized Advertising with Global Level Constraints OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment

Reference 7

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Observation 05aba46a-7061-4d35-9e6e-38f9eb6511fd · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 8

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Observation 87364c22-f810-49b5-b633-040fdb8ca1de · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 9

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Observation a9c21950-92c0-49b3-acb7-1438590772b1 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 10

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Observation 813bf57a-a981-4cfe-8173-c94b262d1e35 · outbound

This paper cites OneSug: The Unified End-to-End Generative Framework for E-commerce Query Suggestion.

Generative Optimization for Incentivized Advertising with Global Level Constraints OneSug: The Unified End-to-End Generative Framework for E-commerce Query Suggestion

Reference 11

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Observation 25037740-20e2-4f0b-b2b5-cf3755d91df4 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 12

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Observation 7b7389fb-ea9b-4134-94e8-efc717943ca7 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 13

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Observation 3fab1a40-f7bf-4e65-8059-b7d20e10a7a3 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 14

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Observation 38494691-2223-4a0c-9007-610cfbe2dde5 · outbound

This paper cites TABBIE: Pretrained Representations of Tabular Data.

Generative Optimization for Incentivized Advertising with Global Level Constraints TABBIE: Pretrained Representations of Tabular Data

Reference 15

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Observation 114d1e68-3470-4a33-aa7a-cb73a412e468 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 16

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2ea6a845-7749-4ff6-ba56-3d7d4c5c3b66 · outbound

This paper cites NumGPT: Improving Numeracy Ability of Generative Pre-trained Models.

Generative Optimization for Incentivized Advertising with Global Level Constraints NumGPT: Improving Numeracy Ability of Generative Pre-trained Models

Reference 17

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 8fc568dd-179b-4c51-a520-c756fc833e6b · outbound

This paper cites Accelerating Offline Reinforcement Learning Application in Real-Time Bidding and Recommendation: Potential Use of Simulation.

Generative Optimization for Incentivized Advertising with Global Level Constraints Accelerating Offline Reinforcement Learning Application in Real-Time Bidding and Recommendation: Potential Use of Simulation

Reference 18

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Observation 25c8b633-cda7-4f16-9e8b-6ad339ad2e8d · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 19

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Observation 1f150a55-0f58-4585-82bd-dae6f21bf373 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Offline Reinforcement Learning with Implicit Q-Learning

Reference 20

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Observation 316a33cc-2eae-4de9-bdb0-60db4f718d79 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 21

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Observation ab759545-ffc9-4d43-b671-a9df39d227d7 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints A Survey on Transformers in Reinforcement Learning

Reference 22

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Observation c2dedaa4-9d53-4763-9b2b-45163a4796d3 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 23

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Observation f92a540e-c230-4a68-b207-28afc8a920c9 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 24

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Observation 85988e6d-13d4-4e44-8e1c-e2dd507a199b · outbound

This paper cites Session-Level Dynamic Ad Load Optimization using Offline Robust Reinforcement Learning.

Generative Optimization for Incentivized Advertising with Global Level Constraints Session-Level Dynamic Ad Load Optimization using Offline Robust Reinforcement Learning

Reference 25

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Observation e5954cc3-0235-48da-93b5-56f3118a73fd · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 26

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Observation 51239714-0a98-4bc2-8b3f-b370a88f25a9 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Generative Regression Based Watch Time Prediction for Short-Video Recommendation

Reference 27

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Observation f1926a53-1162-4218-8314-5ef18155be71 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 28

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Observation 61b22a17-1f76-4fb0-9734-767003c7739c · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 29

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Observation f40f3f42-07d1-4fac-9183-81eb74e04065 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 30

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Observation 1efad25d-793f-4bba-a231-1f61d4e12f27 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 31

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Observation 08cfda64-8295-44e8-96cb-8d7b1083a1bb · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 32

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Observation 1e1002d0-fee3-42ed-8869-43f08702498b · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 33

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Observation 1201809c-eb1b-42f1-9db1-d5af2de3657d · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 34

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Observation 077e3677-b23c-4a70-a245-f3621b19cda3 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 35

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Observation 59bef0d3-4306-44a3-8755-85cfe327cef7 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Do NLP Models Know Numbers? Probing Numeracy in Embeddings

Reference 36

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Observation 6da0be0c-d82a-42e3-b056-3f7419f32731 · outbound

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Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 37

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Observation ec0ab7f1-82b0-47bf-99d2-f6b1ac441671 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 38

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no resolver link, observed 2026-08-07T00:25:19.479043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b69888b2-685d-4d96-bb62-bbc918ed43e1 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c904069d-959b-43c8-b140-762f8fd1ab42 · outbound

This paper cites Off-Policy Primal-Dual Safe Reinforcement Learning.

Generative Optimization for Incentivized Advertising with Global Level Constraints Off-Policy Primal-Dual Safe Reinforcement Learning

Reference 40

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Source-reported events for the cited work

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Observation 964b73c9-0df6-49c8-9f94-12b9275ae12a · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 41

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 03ca3525-e3df-4385-9dcc-b65183d2cbf1 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-07T00:25:20.084361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 14fdb2b6-0acb-4e05-a2b6-ba4d5b80bd2d · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 43

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3c337c75-2ee2-458a-8f5c-9e05697dc30b · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 44

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 734427ea-6d33-4392-aed0-c4dca7fab20f · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 45

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d34ed30c-8a9a-4b83-8103-99a156c4097e · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 46

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 95600353-e9c3-466f-bf22-45aba6bc6d22 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 47

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unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 93371ce6-fbc7-4850-bc7a-9be8834003ed · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-07T00:25:20.012757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 7bc4a26b-349a-4164-8c4c-07ab3a38641a · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 49

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a8f2dfd3-56c3-4eae-8224-4b090f141ed8 · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-07T00:25:19.986189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0ee190b0-62ea-481c-8fbb-0ed1284fac7b · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 51

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:25:19.540996Z digest=sha256:d6b781f21434d2ce19ef5a02553213181036db532d7ca8d6292d9d7a30f22f62

Observation efb11023-08f1-4f7d-8a1e-e4e42b6b1c87 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Generative Optimization for Incentivized Advertising with Global Level Constraints Proximal Policy Optimization Algorithms

Reference 2017

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:25:19.453210Z digest=sha256:205e33b6d562e820b6edc05e5e57adec1345654424ebb5332c6ba20624a237ea

Observation 6dcc2e93-73da-420e-accb-65c2e7e7056e · outbound

This paper cites InProceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining.

Generative Optimization for Incentivized Advertising with Global Level Constraints InProceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:25:19.960403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:25:19.545945Z digest=sha256:c894038cb339b1e20221eda2cd3e7d6a2e9c4ca63a2e566852f242de1be61095

Observation 2cb3f430-6923-4d74-ade7-6bc592789fc7 · outbound

This paper cites InProceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining.

Generative Optimization for Incentivized Advertising with Global Level Constraints InProceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining

Reference 2021

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0c2dc45d-7bbd-48e3-a0c7-946679641e39 · outbound

This paper cites In International conference on machine learning.

Generative Optimization for Incentivized Advertising with Global Level Constraints In International conference on machine learning

Reference 2022

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:25:19.301408Z digest=sha256:7ce770d9b45cd11ec71d86b8d539dbfba38e4462c4dd9ae7d4f84e30c7919932

Observation ca17b1ed-ba18-47ab-bb9c-64433f7a203d · outbound

This paper cites an unresolved cited work.

Generative Optimization for Incentivized Advertising with Global Level Constraints Unresolved cited work

Reference 2023

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:25:19.444294Z digest=sha256:1b58700419beef0c8b9d1988789fa0f511511d1c46e736595dc673cef12f486e

Pith citing papers

No inbound Pith citation observations are available.