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Paper Citation Record · LEDGER

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents

As of 10 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2511.00802.

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

pith.paper-citation-record.v1
2511.00802 v2

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T00:30:42.751522Z

measured 39 of 39 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 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

39 of 39 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved39
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 70231c84-37df-4e64-b3fb-8bad45e78c76 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:37.891373Z digest=sha256:28bea216a3327174ff86d80032c98bdaf06414b88e8cb07dbbf398873471f02d

Observation 5747f842-69ac-4758-bf2a-329578ac5405 · outbound

This paper cites Program Synthesis with Large Language Models.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Program Synthesis with Large Language Models

Reference 2

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source=pdf_text observed=2026-08-04T00:30:38.025346Z digest=sha256:484b5b2984dc8edbb843cbe2877ac99ec2fc0e0a0a8e5dfa62596c35c0f11687

Observation d0929453-0725-4f45-97af-0e5499f6c402 · outbound

This paper cites Never Give Up: Learning Directed Exploration Strategies.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Never Give Up: Learning Directed Exploration Strategies

Reference 3

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source=pdf_text observed=2026-08-04T00:30:38.113645Z digest=sha256:4a99db9290ec3740fd7556286f961774c320fa666ad5a35c06d0224f5e456894

Observation 414fb8ab-1696-4d62-97fa-ceff306e0829 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 4

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:38.222761Z digest=sha256:4229cbab9673702a242192e5af5cd9c3f54a1f70eba1f76c343e67c7af7b7125

Observation 626cc5ce-a372-4ce3-b23f-9b052cccf386 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 5

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source=pdf_text observed=2026-08-04T00:30:38.324453Z digest=sha256:c4545e67cd41ca44990fd2972258660a3783bfe91f7a10f9691e00d780964eb1

Observation d9bf3ec2-fbf0-4651-ae79-ad3fa87a46f7 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:38.465167Z digest=sha256:edf79a97cf6d4581945f908cfb8f5edcc0ea88a5bcc651a544a74866471e857e

Observation bcfa4aad-4bb1-4926-a85d-54ac012cb722 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Evaluating Large Language Models Trained on Code

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:38.619646Z digest=sha256:f2ec574dd3f1f8647d83831d195ed874e3cdfc25c388e0701ad8e88ce5c09ebe

Observation 06bbab86-ce7f-4452-bb52-1c7967754f44 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 8

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:38.821160Z digest=sha256:48a6f325b80469846b032d1e64ec215bef8131a003bceb7de2c24b9b244251ef

Observation a0528a24-8811-41d9-a073-4e4d45366ec7 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 9

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source=pdf_text observed=2026-08-04T00:30:38.991538Z digest=sha256:484fa35b69b91bd0d9b670c10466b1934f44a1962419017c16f9a76cef96e7f7

Observation c11a8765-583a-4c1b-b023-2ba0dd4edc54 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 10

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source=pdf_text observed=2026-08-04T00:30:39.129248Z digest=sha256:a0a6f49956853e552da02fba0ca60dc89af351160657a517721c5cce1f7bb1ea

Observation 4241ee22-d3f3-4092-b22e-7416d9127eda · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 11

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:39.300674Z digest=sha256:15194400fdf8c086d23694857cdc05931caead5de59a1ab64b9898064b26eda6

Observation 7f1bf5b1-076c-47ba-b818-0ac6adc166ec · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 12

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source=pdf_text observed=2026-08-04T00:30:39.491529Z digest=sha256:3f3516f75df364fe77c5d02c0e246947218e6a6dbf7d492991949b7a3f3c4b20

Observation 50c2ab46-44d4-45cb-91df-da9e9761d085 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 13

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:39.621961Z digest=sha256:4bfe75d2814b6a79f0d0cb36e9f41400ef8754e046e22b53141bd1cf6a226292

Observation 97d766ee-0e8c-4e3d-99f4-56a1747273c2 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:39.792993Z digest=sha256:c27aa504a87b9a77bea954b7dbb628d04e3ab38be0ddf232edb64fa7e8c28776

Observation 4c065214-9835-4c31-b0d8-53d82709a5b5 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:39.980233Z digest=sha256:01014786d272dc3c8efe81cae0a50e426ea4b94c733aa2e3f54abf398ab3d530

Observation 04e9f87e-b93f-4a7f-b592-cc28b738610b · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:40.162273Z digest=sha256:499803e0a4cb2a8282ff1fcf5402fd212519f55c71aa738bf53c51610e0c2062

Observation 3a9dfbad-3d5c-4c91-86a8-6fbe11742e78 · outbound

This paper cites How Effective are Large Language Models in Generating Software Specifications?.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents How Effective are Large Language Models in Generating Software Specifications?

Reference 17

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:40.301164Z digest=sha256:451fcf3554348ab149607eeae918853529131d0fb5e9e6234fc69073cce37879

Observation 3bac3897-a42f-4e72-91d5-57bf21784367 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 18

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:40.432408Z digest=sha256:6aed4ab45c4222a1d47428379bda769da28515ffd1f990271f89f0a6f6d36491

Observation 4967cf59-4a28-4558-9941-94123a3fa61f · outbound

This paper cites SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation

Reference 19

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:40.618251Z digest=sha256:6f98a48b231689a7bc7f72d1de0659a2ea0ee43dac322a1d5f97897e37e172ad

Observation 9979a6ff-0f27-48e9-8c34-df3f628233c3 · outbound

This paper cites 2020.Trustworthy online controlled experiments: A practical guide to a/b testing.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents 2020.Trustworthy online controlled experiments: A practical guide to a/b testing

Reference 20

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source=pdf_text observed=2026-08-04T00:30:40.788999Z digest=sha256:f518b50f1b6ae7b947abd40e12a096ac3cc5ad02e9f8e8e9ad5c56a391669bd4

Observation 1704cd98-4b45-4483-a347-ec602e689fd1 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:40.877999Z digest=sha256:90bb479e434e3c8c2dad0a95280c55566f796df03e0d6c62a63ef529d8bf9d41

Observation b42d5b78-5e46-41d5-a060-6f9ad7657bb0 · outbound

This paper cites RAPGen: An Approach for Fixing Code Inefficiencies in Zero-Shot.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents RAPGen: An Approach for Fixing Code Inefficiencies in Zero-Shot

Reference 22

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source=pdf_text observed=2026-08-04T00:30:40.984672Z digest=sha256:4a3281abb067e5851a186003f6a11674d897ed4d16c0740d49f258434aaa15b2

Observation 4088c6a1-3169-4adb-aaaf-8b1aa0beda0b · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 23

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no resolver link, observed 2026-08-04T00:30:41.105537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:41.105537Z digest=sha256:f2157ebc2780511d7d7cc93c589f232949f0e33323278e3e8be23094fd9e6f07

Observation 2ee537c8-2e0e-4168-8ecb-674668b993a6 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 24

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:41.210172Z digest=sha256:03d2a0c8e48536fdbba9c19e75f6dfbd48a1f883b1602fa04906a17b071588f5

Observation 33beb4b8-eb0c-4abc-89c0-6f52516c4833 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 25

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source=pdf_text observed=2026-08-04T00:30:41.342531Z digest=sha256:a888885d63eab1051189fbabb8faeeeb5b16335b53ca3af321779f523828bc8a

Observation 48b08b01-d849-4060-aa5e-92c330ce0668 · outbound

This paper cites Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation

Reference 26

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source=pdf_text observed=2026-08-04T00:30:41.466085Z digest=sha256:f64c84fb0becb247bf6585973153b106dea019d2020f42f9b0d8e8e9a01c7e24

Observation 6965ce0c-b5ef-4115-9026-3321ca29bbf9 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 27

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:41.546154Z digest=sha256:20133742f687fe4537a94edad9f6d6cebde2d85354111eecd17f6831797adff7

Observation 557ef91f-ecba-4fcc-9186-411961897337 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-04T00:30:41.674958Z digest=sha256:af8c6271002f612f0d3a1540ce67f1b34336f27b6a2ea29abdfa082f2e8fe0af

Observation 5557b768-d6b3-4a6b-8d75-43362034afbc · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 29

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:41.762114Z digest=sha256:b9db8d3d9f913ad623978c6d81aa1c4d4468b24a9a20060ff8799477292b9a81

Observation a16c939b-bb9b-4a0c-b73d-e7a4d317a144 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 30

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source=pdf_text observed=2026-08-04T00:30:41.772882Z digest=sha256:d84e3b85812d74866c64b55d49c8eac77e388bd6b7e9d4ea779651b70c4f3def

Observation 90299fa1-b76e-48b7-bc0b-5c202c8148f9 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 31

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source=pdf_text observed=2026-08-04T00:30:41.865812Z digest=sha256:f2e2d33f2c15edbe0ee339cbcd98e04368dd1568cdde3da0e3805a483267ea16

Observation da94cf37-8f8e-4aee-9433-17f0d29addaa · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 32

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:41.987578Z digest=sha256:25b4c0d0fb1e4157ce7ee9ed54404d47cdd42abc073427597cee0537afcbcd31

Observation fcb417b0-945c-4f23-a185-22671bba7419 · outbound

This paper cites A Review of Off-Policy Evaluation in Reinforcement Learning.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents A Review of Off-Policy Evaluation in Reinforcement Learning

Reference 33

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source=pdf_text observed=2026-08-04T00:30:42.106294Z digest=sha256:4088bd920e65611bc4cd0485386703631fbde7df1b01cb6a60b83708c92bfc6e

Observation 4e540948-308f-4fb1-aded-0ff8aadd45aa · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 34

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.201322Z digest=sha256:124163cebedfc104222b54506890574281ec8d241757c4824855214671681aee

Observation c5817083-e42e-431b-8158-0c4f51e649ee · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 35

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.237186Z digest=sha256:f3c5bdbe3d191ff26615fd64c5f3192e6c8fed0294fcccc5617a6ad43b4f7ea2

Observation 3178c37c-46fb-49de-a895-a14fdec12075 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 36

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.330454Z digest=sha256:856cb791bb39c068aa166ed0b9290589177dc6cfc431527847404596b3e34d31

Observation 9954aec3-8bd2-472e-8888-7f0afed41f82 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 37

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no resolver link, observed 2026-08-04T00:30:42.438177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.438177Z digest=sha256:86b9cb7fa3d811f9d0d97a175069595a157158671a473a362e8679150fc85df7

Observation 713e1c19-5162-4849-95eb-c1221ed71520 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 38

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.585562Z digest=sha256:d15f4449707c682b5ef81fa49fc9564e4f779151d8c923a89d3884dd64a7dc1f

Observation 3cb9d77d-11dd-4039-976c-d8942339e669 · outbound

This paper cites an unresolved cited work.

GrowthHacker: Automated Off-Policy Evaluation Optimization Using Code-Modifying LLM Agents Unresolved cited work

Reference 39

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no resolver link, observed 2026-08-04T00:30:42.751522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T00:30:42.751522Z digest=sha256:ef242b7664884fbbb6ecc58effb5b4ec12134d9b3833d77403abb31ac4b4fa9a

Pith citing papers

No inbound Pith citation observations are available.